Triple
T7641759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tomb of Jan Baba |
E173025
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object |
Jan Baba
Jan Baba is a historical figure commemorated by a tomb that bears his name, indicating his local or cultural significance.
|
E678555
|
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: Jan Baba | Statement: [Tomb of Jan Baba, namedAfter, Jan Baba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jan Baba Context triple: [Tomb of Jan Baba, namedAfter, Jan Baba]
-
A.
Baba
Baba is the wealthy, principled yet emotionally distant father of Amir in the film adaptation of "The Kite Runner."
-
B.
Baba
Baba is an honorific title used in South Asian cultures, particularly in Sikh and Punjabi traditions, to denote respect for an elder, spiritual leader, or revered figure.
-
C.
Babu
Babu was a hereditary aristocratic title used by the ruling family of the Jagdishpur estate in India.
-
D.
Baba Malay
Baba Malay is a creole language historically spoken by the Peranakan (Straits Chinese) community, blending Malay with significant Hokkien Chinese and other linguistic influences.
-
E.
Baba the Turk
Baba the Turk is a bearded lady and flamboyant character in Igor Stravinsky’s opera *The Rake’s Progress*, known for her comic yet unsettling marriage to the protagonist Tom Rakewell.
- 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: Jan Baba Triple: [Tomb of Jan Baba, namedAfter, Jan Baba]
Generated description
Jan Baba is a historical figure commemorated by a tomb that bears his name, indicating his local or cultural significance.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jan Baba Target entity description: Jan Baba is a historical figure commemorated by a tomb that bears his name, indicating his local or cultural significance.
-
A.
Baba
Baba is the wealthy, principled yet emotionally distant father of Amir in the film adaptation of "The Kite Runner."
-
B.
Baba
Baba is an honorific title used in South Asian cultures, particularly in Sikh and Punjabi traditions, to denote respect for an elder, spiritual leader, or revered figure.
-
C.
Babu
Babu was a hereditary aristocratic title used by the ruling family of the Jagdishpur estate in India.
-
D.
Baba Malay
Baba Malay is a creole language historically spoken by the Peranakan (Straits Chinese) community, blending Malay with significant Hokkien Chinese and other linguistic influences.
-
E.
Baba the Turk
Baba the Turk is a bearded lady and flamboyant character in Igor Stravinsky’s opera *The Rake’s Progress*, known for her comic yet unsettling marriage to the protagonist Tom Rakewell.
- 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_69c6995360188190968ee57b72a1627f |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6facefbe08190882bd76cf3cd605e |
completed | March 27, 2026, 9:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c870d1008c8190898a582a82038e48 |
completed | March 29, 2026, 12:22 a.m. |
| NEDg | Description generation | batch_69c8735af3b881908459a94c4d25e339 |
completed | March 29, 2026, 12:33 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c8745f29608190aca3bbfe76a877a1 |
completed | March 29, 2026, 12:37 a.m. |
Created at: March 27, 2026, 3:58 p.m.