Triple
T23650313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alcon |
E584149
|
entity |
| Predicate | servesSpecialty |
P48322
|
FINISHED |
| Object | ophthalmology |
—
|
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: ophthalmology | Statement: [Alcon, servesSpecialty, ophthalmology]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesSpecialty Context triple: [Alcon, servesSpecialty, ophthalmology]
-
A.
hasSpecialtyFood
Indicates that an entity offers, serves, or is associated with a particular type of specialty food.
-
B.
isTypicallyServedFor
Indicates that one item is most commonly or customarily served as a meal or course for the other (e.g., a dish typically served for breakfast, lunch, or dinner).
-
C.
servesType
chosen
Indicates that one entity provides, offers, or is used to deliver a particular type, category, or kind of thing or service.
-
D.
servesMostly
Indicates that one entity primarily functions to serve, support, or cater to another entity, more than to any other.
-
E.
servesProduct
Indicates that one entity provides or offers a particular product to others, typically in a commercial or service context.
- 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_69e248fefafc81909656921192f30e80 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b2885b408190a43dfed93309a4d6 |
completed | April 29, 2026, 7:26 a.m. |
| PD | Predicate disambiguation | batch_69f118d7903c8190bb590a71771e93af |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:49 p.m.