Triple
T3995046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camponotus pennsylvanicus |
E87078
|
entity |
| Predicate | queenLength |
P53730
|
FINISHED |
| Object | 15 to 17 millimeters |
—
|
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: 15 to 17 millimeters | Statement: [Camponotus pennsylvanicus, queenLength, 15 to 17 millimeters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: queenLength Context triple: [Camponotus pennsylvanicus, queenLength, 15 to 17 millimeters]
-
A.
numberOfKings
Indicates the quantity of entities that hold the role or title of king in a given context.
-
B.
hasQueenCaste
Indicates that an entity possesses or includes a queen caste within its social or organizational structure.
-
C.
laterNumberOfKnights
Indicates that one entity has a greater (later or higher) number of knights than another entity in a comparative context.
-
D.
queenRepresentedBy
Indicates that a queen is formally depicted, symbolized, or acted for by a particular representative entity.
-
E.
hasCrownCount
Indicates the number of crowns that an entity possesses or is associated with.
- 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_69aed94118148190975e6aa4e554cde9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb81040481909b22e4c445ecae0f |
completed | March 9, 2026, 4:55 p.m. |
| PD | Predicate disambiguation | batch_69aef8f692008190bf4d637ffc3d3eaa |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aefb7f92348190ae35f1d75b0b5d4f |
completed | March 9, 2026, 4:55 p.m. |
Created at: March 9, 2026, 3:34 p.m.