Triple
T13507631
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Mexican |
E321052
|
entity |
| Predicate | hasTitleObjectInPlot |
P110033
|
FINISHED |
| Object | The Mexican pistol |
—
|
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: The Mexican pistol | Statement: [The Mexican, hasTitleObjectInPlot, The Mexican pistol]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTitleObjectInPlot Context triple: [The Mexican, hasTitleObjectInPlot, The Mexican pistol]
-
A.
hasTitleIn
Indicates that an entity holds or is associated with a specific title within a particular context, domain, or language.
-
B.
hasTitleFeature
Indicates that an entity possesses a specific characteristic, attribute, or element related to its title.
-
C.
hasTitleFrom
Indicates that one entity holds or uses a title that originates from, or is conferred by, another entity.
-
D.
containsTitle
Indicates that one entity includes or holds another entity’s title as part of its content or metadata.
-
E.
hasTitleSubject
Indicates that an entity has a specific subject or topic as the focus of its title.
- 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_69d807629d6c8190998f1b9bb12d2ed0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaf8259a08190ada13c4a3078f07d |
completed | April 12, 2026, 2:43 p.m. |
| PD | Predicate disambiguation | batch_69dbae0b63748190b5e207f84b2532ea |
completed | April 12, 2026, 2:36 p.m. |
| PDg | Predicate description generation | batch_69dbaee128d88190b097be17fdd2f92b |
completed | April 12, 2026, 2:40 p.m. |
Created at: April 9, 2026, 9:43 p.m.