Triple
T10573453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ixtapa-Zihuatanejo |
E249550
|
entity |
| Predicate | touristDevelopmentBegan |
P45842
|
FINISHED |
| Object | 1970s |
—
|
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: 1970s | Statement: [Ixtapa-Zihuatanejo, touristDevelopmentBegan, 1970s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: touristDevelopmentBegan Context triple: [Ixtapa-Zihuatanejo, touristDevelopmentBegan, 1970s]
-
A.
beganDiversificationIntoTourism
Indicates that an entity started expanding its activities or operations into the tourism sector from a certain point in time.
-
B.
developedAsTouristAttractionBy
Indicates that an entity was created, enhanced, or promoted as a tourist attraction by a specific agent or organization.
-
C.
tourismDevelopmentLevel
Indicates the extent or intensity to which tourism-related infrastructure, services, and activities have been developed in a given area.
-
D.
tourismBoom
chosen
Indicates a rapid and significant increase in tourism activity, such as visitor numbers, spending, or development, within a particular place or period.
-
E.
hasDevelopmentTour
Indicates that an entity organizes, participates in, or is associated with a development-focused tour, typically for training, preparation, or early-stage exposure.
- 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_69d381c8bd708190acf3d275c908251e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d5274929cc81909a79d5e2049f7389 |
completed | April 7, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69d51901ff6c819095e7b528170a69dc |
completed | April 7, 2026, 2:47 p.m. |
Created at: April 6, 2026, 12:37 p.m.