Triple
T12685451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Craig Wood |
E303054
|
entity |
| Predicate | edited |
P1932
|
FINISHED |
| Object | The Mexican |
E321052
|
NE 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 | Statement: [Craig Wood, edited, The Mexican]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Mexican Context triple: [Craig Wood, edited, The Mexican]
-
A.
The Mexican
chosen
The Mexican is a 2001 crime-comedy film starring Brad Pitt and Julia Roberts that blends romance, dark humor, and a quirky road-trip plot centered around a legendary cursed pistol.
-
B.
Mexicana
Mexicana is a themed area at Chessington World of Adventures that recreates a Wild West-style Mexican frontier town with rides, attractions, and entertainment.
-
C.
Mexicanero
Mexicanero are an Indigenous Nahua-speaking people of western Mexico, primarily living in the state of Nayarit and surrounding regions.
-
D.
Mejicanos
Mejicanos is a densely populated municipality in the San Salvador department of El Salvador, forming part of the greater San Salvador metropolitan area.
-
E.
MEX
MEX is the IATA airport code for Mexico City International Airport, the main international gateway serving Mexico City and one of the busiest airports in Latin America.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d7bdee64a08190801c6d470aefd723 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961d7cd4c81909521839ef5859799 |
completed | April 10, 2026, 8:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f671a8f068819086e2191439607f76 |
completed | May 2, 2026, 9:50 p.m. |
Created at: April 9, 2026, 5:21 p.m.