Triple
T30933338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mindy Lahiri |
E788052
|
entity |
| Predicate | hasProfessionSpecialty |
P466
|
FINISHED |
| Object | obstetrics |
—
|
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: obstetrics | Statement: [Mindy Lahiri, hasProfessionSpecialty, obstetrics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProfessionSpecialty Context triple: [Mindy Lahiri, hasProfessionSpecialty, obstetrics]
-
A.
hasSpecialty
chosen
Indicates that an entity possesses a particular area of expertise, focus, or professional specialization.
-
B.
hasSpecialist
Indicates that one entity is associated with or assigned to a specialist entity that provides expert support, service, or oversight for it.
-
C.
hasSpecialistStatus
Indicates that an entity holds a recognized specialist designation or status in a particular field, role, or context.
-
D.
isConsideredSpecialtyOf
Indicates that one field, practice, or area of expertise is regarded as a specialized branch or subset of another broader field.
-
E.
hasGivenProfession
Indicates that an entity holds or practices a specified profession or occupation.
- F. None of above.
Provenance (3 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_69f224c0b7fc819090cb89df60d23653 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a001adc8c108190ab3a43f6415e2be3 |
completed | May 10, 2026, 5:42 a.m. |
| PD | Predicate disambiguation | batch_6a001a290330819097c2c3123f9014b4 |
completed | May 10, 2026, 5:39 a.m. |
Created at: April 29, 2026, 8:52 p.m.