Triple
T3475911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bornean orangutan |
E73373
|
entity |
| Predicate | maleCharacteristic |
P18326
|
FINISHED |
| Object | cheek pads (flanges) |
—
|
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: cheek pads (flanges) | Statement: [Bornean orangutan, maleCharacteristic, cheek pads (flanges)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maleCharacteristic Context triple: [Bornean orangutan, maleCharacteristic, cheek pads (flanges)]
-
A.
maleEquivalent
Indicates that one entity is the corresponding male counterpart or equivalent of another entity.
-
B.
maleCalled
Indicates that a male individual is referred to or named by a particular name or label.
-
C.
malesOftenHave
chosen
Indicates that male entities frequently possess, exhibit, or are associated with the specified attribute or characteristic.
-
D.
maleLength
Indicates that the relationship specifies the length or size measurement of a male individual or male part of an entity.
-
E.
featuredGender
Indicates that a particular gender is highlighted, emphasized, or given primary focus in a given context or presentation.
- 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.