Triple
T3475904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bornean orangutan |
E73373
|
entity |
| Predicate | mainCauseOfHabitatLoss |
P11752
|
FINISHED |
| Object | palm oil plantations |
—
|
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: palm oil plantations | Statement: [Bornean orangutan, mainCauseOfHabitatLoss, palm oil plantations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainCauseOfHabitatLoss Context triple: [Bornean orangutan, mainCauseOfHabitatLoss, palm oil plantations]
-
A.
terrestrialVertebrateSpeciesLoss
Indicates the reduction or disappearance of species of land-dwelling vertebrate animals within a given area or time period.
-
B.
humanImpact
chosen
Indicates the effect or influence that human activities have on another entity, system, or environment.
-
C.
extinctionReason
Indicates the cause or factor responsible for an entity’s extinction.
-
D.
ecoregionInfluence
Indicates that one ecoregion affects or shapes the environmental characteristics, processes, or conditions of another area or system.
-
E.
conservationIssue
Indicates that an entity is associated with a problem, threat, or concern related to the protection, preservation, or sustainable management of natural resources or biodiversity.
- 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_69ad85b2fed48190948c8765e453d270 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbb593a388190b7786190deba96ed |
completed | March 8, 2026, 6:09 p.m. |
| PD | Predicate disambiguation | batch_69adae07802c8190919c49b0e65b2797 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:17 p.m.