Triple
T3670881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joseph Needham |
E77874
|
entity |
| Predicate | hasConcept |
P531
|
FINISHED |
| Object |
Needham Question
The Needham Question is a famous inquiry posed by historian Joseph Needham about why modern science and industrialization developed in Europe rather than in China, despite China’s earlier technological and scientific achievements.
|
E376865
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Needham Question | Statement: [Joseph Needham, hasConcept, Needham Question]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Needham Question Context triple: [Joseph Needham, hasConcept, Needham Question]
-
A.
Nehase
Nehase is the twelfth month of the Ethiopian calendar, corresponding roughly to August in the Gregorian calendar.
-
B.
Nafe
Nafe is an indigenous Oceanic language spoken in Vanuatu.
-
C.
Nesta
Nesta is the middle name of legendary Jamaican reggae musician and cultural icon Bob Marley.
-
D.
Nedmag
Nedmag is a Dutch company specializing in the production of high-quality magnesium salts and related mineral products.
-
E.
Heed
Heed is the fiercely loyal yet conflicted protagonist of Toni Morrison’s novel "Love," whose lifelong bond and rivalry with her friend Christine drive much of the story’s emotional and thematic tension.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Needham Question Triple: [Joseph Needham, hasConcept, Needham Question]
Generated description
The Needham Question is a famous inquiry posed by historian Joseph Needham about why modern science and industrialization developed in Europe rather than in China, despite China’s earlier technological and scientific achievements.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Needham Question Target entity description: The Needham Question is a famous inquiry posed by historian Joseph Needham about why modern science and industrialization developed in Europe rather than in China, despite China’s earlier technological and scientific achievements.
-
A.
Nehase
Nehase is the twelfth month of the Ethiopian calendar, corresponding roughly to August in the Gregorian calendar.
-
B.
Nafe
Nafe is an indigenous Oceanic language spoken in Vanuatu.
-
C.
Nesta
Nesta is the middle name of legendary Jamaican reggae musician and cultural icon Bob Marley.
-
D.
Nedmag
Nedmag is a Dutch company specializing in the production of high-quality magnesium salts and related mineral products.
-
E.
Heed
Heed is the fiercely loyal yet conflicted protagonist of Toni Morrison’s novel "Love," whose lifelong bond and rivalry with her friend Christine drive much of the story’s emotional and thematic tension.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ad85e083008190b2e1b7085fe500bd |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc42c96648190abbd5d23b25d6a6b |
completed | March 8, 2026, 6:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b48850515c8190bdb9ddcfc0a13f4e |
completed | March 13, 2026, 9:57 p.m. |
| NEDg | Description generation | batch_69b48b55ad8081909166e7418cdf0f06 |
completed | March 13, 2026, 10:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b48e1ff9fc8190bb2559b9e55ea2b8 |
completed | March 13, 2026, 10:22 p.m. |
Created at: March 8, 2026, 3:25 p.m.