Triple
T23704643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prophet Sulayman smiles at the ant’s words |
E585683
|
entity |
| Predicate | featuresArmy |
P7256
|
FINISHED |
| Object | Sulayman’s forces of humans, jinn, and birds |
—
|
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: Sulayman’s forces of humans, jinn, and birds | Statement: [Prophet Sulayman smiles at the ant’s words, featuresArmy, Sulayman’s forces of humans, jinn, and birds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresArmy Context triple: [Prophet Sulayman smiles at the ant’s words, featuresArmy, Sulayman’s forces of humans, jinn, and birds]
-
A.
militaryCharacteristic
chosen
Indicates that one entity possesses a specific military-related attribute, quality, or feature in relation to another entity or context.
-
B.
mentionsArmy
Indicates that one entity explicitly refers to or brings up an army in relation to another entity.
-
C.
typeOfTroops
Indicates the specific category or kind of military forces involved in or associated with an entity or event.
-
D.
groundForces
Indicates that one entity deploys, commands, or involves military forces operating on land in relation to another entity or context.
-
E.
servedArmy
Indicates that an entity has performed military service in, or been a member of, a particular army.
- 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_69e24904bd508190abfcb74855de2918 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b685dfc8819081906aceab7b0bdd |
completed | April 29, 2026, 7:43 a.m. |
| PD | Predicate disambiguation | batch_69f155d5265881908e43a9696b6a6d0f |
completed | April 29, 2026, 12:50 a.m. |
Created at: April 17, 2026, 6:53 p.m.