Triple
T6333532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bengal tiger |
E142435
|
entity |
| Predicate | mostNumerousSubspeciesOf |
P70911
|
FINISHED |
| Object | tiger |
—
|
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: tiger | Statement: [Bengal tiger, mostNumerousSubspeciesOf, tiger]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mostNumerousSubspeciesOf Context triple: [Bengal tiger, mostNumerousSubspeciesOf, tiger]
-
A.
recognizedSubspeciesCount
Indicates the number of subspecies that are formally recognized for a given species or taxon.
-
B.
subspeciesOf
Indicates that one taxonomic group is a subspecific rank within, and directly derived from, another species.
-
C.
isMostNumerousBirdSpecies
Indicates that the subject bird species has the largest population size compared to all other bird species in the relevant context.
-
D.
numberOfSpecies
Indicates the count of distinct species associated with a given entity or context.
-
E.
speciesNumber
Indicates the numerical identifier or count associated with a particular species in a given context.
- F. None of above. chosen
Provenance (4 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_69c008d4d8e88190ad301c05b08722ac |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06517a1e88190a0bfcac8a7e3a305 |
completed | March 22, 2026, 9:54 p.m. |
| PD | Predicate disambiguation | batch_69c060e7e2d48190af9d004236466788 |
completed | March 22, 2026, 9:36 p.m. |
| PDg | Predicate description generation | batch_69c064c080148190a7c3218867f1f572 |
completed | March 22, 2026, 9:53 p.m. |
Created at: March 22, 2026, 4:30 p.m.