Triple
T16407895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aphaenogaster |
E398482
|
entity |
| Predicate | hasWorkerSize |
P121329
|
FINISHED |
| Object | small to medium |
—
|
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: small to medium | Statement: [Aphaenogaster, hasWorkerSize, small to medium]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWorkerSize Context triple: [Aphaenogaster, hasWorkerSize, small to medium]
-
A.
hasWorker
Indicates that one entity employs, utilizes, or is associated with another entity in the role of a worker.
-
B.
workerSize
chosen
Indicates the number of workers or the scale of a workforce associated with an entity.
-
C.
hasWorkCount
Indicates the number of works (such as items, creations, or outputs) associated with a given entity.
-
D.
hasWorkerPolymorphism
Indicates that an entity supports multiple interchangeable worker implementations or roles that can perform the same task in different ways.
-
E.
hasSize
Indicates that one entity possesses a particular physical magnitude or extent, such as length, volume, or overall dimensions.
- 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_69d87f2950248190bc8ad9b9bebdc8c8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32870e44c8190aae7bc6e6022ceb7 |
completed | April 18, 2026, 6:45 a.m. |
| PD | Predicate disambiguation | batch_69e226fe1dd08190865c181721f8c348 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:09 a.m.