Triple
T30994519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palawan faunal region |
E789757
|
entity |
| Predicate | faunalSimilarityWith |
P94757
|
FINISHED |
| Object | Borneo |
—
|
NE NERFINISHED |
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: Borneo | Statement: [Palawan faunal region, faunalSimilarityWith, Borneo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: faunalSimilarityWith Context triple: [Palawan faunal region, faunalSimilarityWith, Borneo]
-
A.
speciesResemblance
Indicates that one species shares notable similarities in appearance or characteristics with another species.
-
B.
consideredConspecificWith
Indicates that two organisms are regarded as belonging to the same species or treated as the same species for classification or analysis purposes.
-
C.
hasSimilarityTo
chosen
Indicates that one entity shares common characteristics, features, or qualities with another entity to a notable degree.
-
D.
simulatesHabitatOf
Indicates that one entity artificially recreates or models the living conditions or environment characteristic of another entity’s natural habitat.
-
E.
namedForSimilarityTo
Indicates that one entity is given its name because of a perceived resemblance or likeness to another entity.
- 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_69f224c65a348190baaed1c01a29900c |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6953bafb88190a860e9c68a3dd4b2 |
completed | May 3, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69f690ef92308190903a54fc74233269 |
completed | May 3, 2026, 12:03 a.m. |
Created at: April 29, 2026, 8:56 p.m.