Triple
T36953259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lancer assault rifle |
E914127
|
entity |
| Predicate | iconicWeaponOf |
P7745
|
FINISHED |
| Object | Marcus Fenix |
—
|
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: Marcus Fenix | Statement: [Lancer assault rifle, iconicWeaponOf, Marcus Fenix]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: iconicWeaponOf Context triple: [Lancer assault rifle, iconicWeaponOf, Marcus Fenix]
-
A.
weaponOfInterest
Indicates that an entity is a weapon that is specifically relevant, notable, or targeted for attention within a given context or scenario.
-
B.
hasNotableWeaponNamedAfter
Indicates that an entity possesses a notable weapon that is named after another specific entity.
-
C.
weaponUsedIn
Indicates that a particular weapon is employed or involved in carrying out a specific event or action.
-
D.
weaponsRepresent
Indicates that certain weapons serve as symbols or embodiments of something, such as ideas, groups, or values.
-
E.
typicalWeapon
chosen
Indicates that the object is a weapon commonly or characteristically used by the subject.
- 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_69f76e8b28848190abd81fe7a7374910 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fa0a7b00948190a257273d9968c5d7 |
completed | May 5, 2026, 3:19 p.m. |
| PD | Predicate disambiguation | batch_69f9fec9c9488190ae2a349651a02782 |
completed | May 5, 2026, 2:29 p.m. |
Created at: May 3, 2026, 4:13 p.m.