Triple
T18836793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | barasingha recovery program |
E460684
|
entity |
| Predicate | targetsThreat |
P133105
|
FINISHED |
| Object | habitat loss |
—
|
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: habitat loss | Statement: [barasingha recovery program, targetsThreat, habitat loss]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetsThreat Context triple: [barasingha recovery program, targetsThreat, habitat loss]
-
A.
targetOfThreat
Indicates that one entity is the recipient or intended victim of a threat made by another entity.
-
B.
laterThreat
Indicates that one entity poses a threat to another at a time subsequent to some referenced or initial point.
-
C.
recognizesThreat
Indicates that an entity identifies or acknowledges another entity or situation as a potential danger or source of harm.
-
D.
featuresThreat
Indicates that one entity includes, presents, or contains a threat associated with another entity.
-
E.
hasThreats
Indicates that one entity poses or is associated with potential danger, harm, or adverse consequences toward another entity.
- 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_69d8dcfa11e4819090ab1ef5bdcd2b2e |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5a99e86388190957acaaab401b5cb |
completed | April 20, 2026, 4:20 a.m. |
| PD | Predicate disambiguation | batch_69e48d1e7dac81909ea1e758c87773c5 |
completed | April 19, 2026, 8:06 a.m. |
| PDg | Predicate description generation | batch_69e49785fd7081909577e90a55df0a35 |
completed | April 19, 2026, 8:51 a.m. |
Created at: April 10, 2026, 11:56 a.m.