Triple
T13567652
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tubbataha Reef |
E324079
|
entity |
| Predicate | numberOfCoralSpeciesApproximate |
P6211
|
FINISHED |
| Object | about 360 |
—
|
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: about 360 | Statement: [Tubbataha Reef, numberOfCoralSpeciesApproximate, about 360]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCoralSpeciesApproximate Context triple: [Tubbataha Reef, numberOfCoralSpeciesApproximate, about 360]
-
A.
numberOfSpecies
chosen
Indicates the count of distinct species associated with a given entity or context.
-
B.
reefType
Indicates the specific classification or category of reef associated with an entity.
-
C.
numberOfCays
Indicates the quantity of cays (small low-elevation islands or sandbanks) associated with or contained within a given geographic entity.
-
D.
numberOfIslandsAndReefs
Indicates the count of islands and reefs associated with or contained within a given geographic or administrative entity.
-
E.
speciesNumber
Indicates the numerical identifier or count associated with a particular species in a given context.
- 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_69d8076830b48190910a902bae5888e2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb00e0188819094fde44f85adb69c |
completed | April 12, 2026, 2:45 p.m. |
| PD | Predicate disambiguation | batch_69dbae161a0481909f9d3f40ca4e0ac5 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:48 p.m.