Triple
T14491455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | chital |
E359370
|
entity |
| Predicate | oftenAssociatesWith |
P3100
|
FINISHED |
| Object | langurs |
—
|
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: langurs | Statement: [chital, oftenAssociatesWith, langurs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenAssociatesWith Context triple: [chital, oftenAssociatesWith, langurs]
-
A.
associatedWithSee
Indicates a relationship where one entity is contextually or functionally linked to another through the act or concept of seeing or visual observation.
-
B.
isAssociatedWith
Indicates that there exists a connection, relationship, or involvement between two entities without specifying its exact nature.
-
C.
oftenAccompaniedBy
chosen
Indicates that one entity is frequently found together with, occurs alongside, or is commonly associated in presence or use with another entity.
-
D.
associatedWithAssociation
Indicates a relationship where an entity is linked or connected to a particular association or organization.
-
E.
associatedWithUse
Indicates a relationship where one entity is connected to or involved in the use or utilization of another entity.
- 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_69d8279740308190af9df93a3af8592e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de930d820481908b9813014dd02540 |
completed | April 14, 2026, 7:18 p.m. |
| PD | Predicate disambiguation | batch_69de5c4ccba08190a988bfda0bc9f5cb |
completed | April 14, 2026, 3:25 p.m. |
Created at: April 10, 2026, 1:20 a.m.