Triple
T28398485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | al-Nuʿman ibn Muqarrin |
E719341
|
entity |
| Predicate | opponentAtBattle |
P18835
|
FINISHED |
| Object | Sasanian Empire |
—
|
NE NERFINISHED |
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: Sasanian Empire | Statement: [al-Nuʿman ibn Muqarrin, opponentAtBattle, Sasanian Empire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: opponentAtBattle Context triple: [al-Nuʿman ibn Muqarrin, opponentAtBattle, Sasanian Empire]
-
A.
battleOpponent
chosen
Indicates that two entities are engaged in or designated as opponents in a battle or combat scenario.
-
B.
opponentInScenario
Indicates that one entity is an adversary or rival of another within a specific scenario, context, or situation.
-
C.
partnerInBattle
Indicates that two entities are allied or cooperate as partners in the same battle or combat engagement.
-
D.
associatedOpponent
Indicates that one entity is recognized or designated as an opponent or adversary associated with another entity in a given context.
-
E.
facedOpponent
Indicates that one entity directly confronted or competed against another as an opponent in a contest, conflict, or challenge.
- 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_69eff6efd1b08190ae3cefd4f11388a2 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f6691f5e188190b12c7b2eb729a45e |
completed | May 2, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69f6659b62fc8190b21555d0ba54db2d |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 28, 2026, 1:18 a.m.