Triple
T11432132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas White |
E270909
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Thomas
Thomas is a common masculine given name of Aramaic origin, traditionally interpreted to mean "twin" and widely used in many English-speaking and European countries.
|
E67625
|
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: Thomas | Statement: [Thomas White, givenName, Thomas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thomas Context triple: [Thomas White, givenName, Thomas]
-
A.
John
John is a masculine given name of Hebrew origin, widely used in English-speaking countries and borne by numerous historical and contemporary figures.
-
B.
John
John is the given name of John Reith, the influential first Director-General of the BBC who shaped early public service broadcasting in the United Kingdom.
-
C.
John
John is the given name of the American composer John Luther Adams, known for his works inspired by nature and environmental themes.
-
D.
John
John is the given name of actor John Cho, a Korean American performer known for roles in the "Harold & Kumar" films and the "Star Trek" reboot series.
-
E.
John
John is the first name of the fictional character John Connor, the prophesied leader of the human resistance in the Terminator franchise.
- 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: Thomas Triple: [Thomas White, givenName, Thomas]
Generated description
Thomas is a common masculine given name of Aramaic origin, traditionally interpreted to mean "twin" and widely used in many English-speaking and European countries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Thomas Target entity description: Thomas is a common masculine given name of Aramaic origin, traditionally interpreted to mean "twin" and widely used in many English-speaking and European countries.
-
A.
Thomas
chosen
Thomas is a common masculine given name of Aramaic origin, widely used in English-speaking and many other cultures.
-
B.
Thomas
Thomas is a common surname of English and Welsh origin, derived from the given name Thomas and borne by numerous notable individuals worldwide.
-
C.
Thomas
Thomas is the given name of Thomas Malthus, the influential English economist and demographer known for his theories on population growth and resource limits.
-
D.
Thomas
Thomas is the given name of Thomas Paine, the influential 18th-century political philosopher and writer known for works like "Common Sense" and "The Rights of Man."
-
E.
Thomas
Thomas is the given first name of English actor Tom Sturridge, known for his work in film, television, and theatre.
- F. None of above.
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_69d6aadeef688190874bcecd88b3dd9b |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d806c30d788190b0c939b33de89277 |
completed | April 9, 2026, 8:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5d36cee548190a8215ba088bdb01a |
completed | April 20, 2026, 7:19 a.m. |
| NEDg | Description generation | batch_69e5d615b6a08190b6000339bec4270d |
completed | April 20, 2026, 7:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e5d924963c8190bfc55ffeb529a499 |
completed | April 20, 2026, 7:43 a.m. |
Created at: April 8, 2026, 9:35 p.m.