Triple
T16553046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panthera tigris |
E402119
|
entity |
| Predicate | largestLivingCatSpecies |
P28614
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Panthera tigris, largestLivingCatSpecies, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: largestLivingCatSpecies Context triple: [Panthera tigris, largestLivingCatSpecies, true]
-
A.
hasLargestSpecies
Indicates that one entity possesses, contains, or is associated with the species that is largest in size or extent within a given group or context.
-
B.
largestLiving
chosen
Indicates that the subject is the largest currently living instance of a given type or within a specified group or context.
-
C.
lionLength
Indicates the length measurement associated with a lion.
-
D.
lionAttribute
Indicates that one entity has an attribute, property, or characteristic related to a lion in relation to another entity.
-
E.
lionOrigin
Indicates that one entity is the geographical or contextual origin of a lion or group of lions.
- 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_69d88384bc30819084229e7dcdc39a41 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e34fc6735481908b59bbf80fb3469b |
completed | April 18, 2026, 9:32 a.m. |
| PD | Predicate disambiguation | batch_69e296a47b7481909d9958158510c806 |
completed | April 17, 2026, 8:23 p.m. |
Created at: April 10, 2026, 5:15 a.m.