Triple
T5974449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mylapore (traditional) |
E132949
|
entity |
| Predicate | traditionallyKnownFor |
P67817
|
FINISHED |
| Object | martyrdom of Thomas the Apostle |
—
|
LITERAL FINISHED |
How this triple was built (2 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: martyrdom of Thomas the Apostle | Statement: [Mylapore (traditional), traditionallyKnownFor, martyrdom of Thomas the Apostle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionallyKnownFor Context triple: [Mylapore (traditional), traditionallyKnownFor, martyrdom of Thomas the Apostle]
-
A.
formerlyKnownFor
Indicates that an entity was previously recognized or notable for a particular role, attribute, or activity, but is no longer primarily associated with it.
-
B.
organFamousFor
Indicates that an organ is widely recognized or notable for a particular characteristic, function, or association.
-
C.
fameFor
Indicates that one entity is widely known or recognized specifically because of, or in connection with, another entity.
-
D.
reconocidaPor
Indicates that an entity is recognized, acknowledged, or honored by another entity.
-
E.
traditionallyUsedBy
Indicates that something has been customarily or historically used by a particular person, group, or culture over time.
- F. None of above. chosen
Provenance (4 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_69c0086deab081908550159ca23eec9b |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04dc2243c8190bd3488e7b24af985 |
completed | March 22, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69c049dcb3c081908ccc9b4d4b210229 |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04dbefd1081909795fe1a812b991a |
completed | March 22, 2026, 8:14 p.m. |
Created at: March 22, 2026, 4:03 p.m.