Triple
T17204254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dorylus |
E417557
|
entity |
| Predicate | soldierMorphology |
P126393
|
FINISHED |
| Object | very large mandibles |
—
|
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: very large mandibles | Statement: [Dorylus, soldierMorphology, very large mandibles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: soldierMorphology Context triple: [Dorylus, soldierMorphology, very large mandibles]
-
A.
militaryCharacteristic
Indicates that one entity possesses a specific military-related attribute, quality, or feature in relation to another entity or context.
-
B.
workerMorphology
Indicates the physical form or structural characteristics of a worker in relation to its role or function.
-
C.
soldierCaste
Indicates that an entity belongs to, or is characterized as part of, a soldier or warrior class within a social or organizational hierarchy.
-
D.
typeOfTroops
Indicates the specific category or kind of military forces involved in or associated with an entity or event.
-
E.
militarySize
Indicates the total number of personnel in a military force, typically including active-duty members and sometimes reserves.
- 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_69d886d6ba8c819093215917b3d01689 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42db1e01c81909db0491fd9f49bed |
completed | April 19, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69e3831e354881908c5505ffd15c84e9 |
completed | April 18, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69e3873f62108190966c4e741ebd548d |
completed | April 18, 2026, 1:29 p.m. |
Created at: April 10, 2026, 5:38 a.m.