Triple
T25144289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cat Ba langur |
E629888
|
entity |
| Predicate | primaryThreatFromHumans |
P23662
|
FINISHED |
| Object | poaching for traditional medicine |
—
|
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: poaching for traditional medicine | Statement: [Cat Ba langur, primaryThreatFromHumans, poaching for traditional medicine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryThreatFromHumans Context triple: [Cat Ba langur, primaryThreatFromHumans, poaching for traditional medicine]
-
A.
threatToHumans
Indicates that the subject poses or represents a potential danger, harm, or risk to humans.
-
B.
primaryThreat
chosen
Indicates that one entity is the main or most significant source of danger, harm, or risk to another entity.
-
C.
conflictsWithHumans
Indicates a relationship where an entity is in opposition, dispute, or hostile interaction with humans, leading to incompatibility or clashes between their interests or actions.
-
D.
impactOnHumans
Indicates a relationship where something produces an effect, influence, or consequence on humans.
-
E.
threatsFaced
Indicates that an entity is exposed to or experiences specific dangers, risks, or harmful conditions.
- 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_69e2ff349e408190a6f4a5a66279f54d |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f6fb19063c81909466b329655c8583 |
completed | May 3, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f6f969b4cc8190afb473a2d8b110bc |
completed | May 3, 2026, 7:29 a.m. |
Created at: April 18, 2026, 6:29 a.m.