Triple
T13567653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tubbataha Reef |
E324079
|
entity |
| Predicate | numberOfFishSpeciesApproximate |
P6211
|
FINISHED |
| Object | over 600 |
—
|
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: over 600 | Statement: [Tubbataha Reef, numberOfFishSpeciesApproximate, over 600]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfFishSpeciesApproximate Context triple: [Tubbataha Reef, numberOfFishSpeciesApproximate, over 600]
-
A.
numberOfSpecies
chosen
Indicates the count of distinct species associated with a given entity or context.
-
B.
percentageOfFreshwaterSpecies
Indicates the proportion (expressed as a percentage) of all considered species that are freshwater species.
-
C.
hasFishingSpecies
Indicates that a location, body of water, or fishing area supports or contains one or more specific species that can be fished there.
-
D.
speciesNumber
Indicates the numerical identifier or count associated with a particular species in a given context.
-
E.
hasFishCountingFacility
Indicates that a location or structure is equipped with a facility specifically designed for counting fish.
- 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.