Triple
T1526360
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pan paniscus |
E32343
|
entity |
| Predicate | closestRelative |
P8563
|
FINISHED |
| Object | Pan troglodytes |
—
|
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: Pan troglodytes | Statement: [Pan paniscus, closestRelative, Pan troglodytes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: closestRelative Context triple: [Pan paniscus, closestRelative, Pan troglodytes]
-
A.
closerTo
Indicates that one entity is at a smaller distance to a reference entity than another entity is.
-
B.
closestLivingRelatives
chosen
Indicates that the related entities are the most closely related to each other among all currently living entities, in terms of evolutionary or genealogical proximity.
-
C.
near
Indicates that one entity is located at a short distance from another entity in space or position.
-
D.
closestApproachTarget
Indicates the entity that another entity comes nearest to during its path or motion.
-
E.
relativePosition
Indicates the spatial relationship of one entity’s location with respect to another entity’s position.
- 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_69a885e9b0ac819093a9806ad0efc82c |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a933ddc5a881909cdf503f2bc29bd4 |
completed | March 5, 2026, 7:42 a.m. |
| PD | Predicate disambiguation | batch_69a907ae8f688190ad9000ea1e018585 |
completed | March 5, 2026, 4:33 a.m. |
Created at: March 4, 2026, 7:26 p.m.