Triple
T2195494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Municipal |
E49961
|
entity |
| Predicate | countryTopLevelStatus |
P33447
|
FINISHED |
| Object | top-tier club in Guatemala |
—
|
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: top-tier club in Guatemala | Statement: [Municipal, countryTopLevelStatus, top-tier club in Guatemala]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryTopLevelStatus Context triple: [Municipal, countryTopLevelStatus, top-tier club in Guatemala]
-
A.
countryStatus
Indicates the political or legal condition of a country, such as its sovereignty, recognition, or current state in international or domestic contexts.
-
B.
countrySpecificStatus
chosen
Indicates a status or condition that is defined or applied specifically in the context of a particular country.
-
C.
regionStatus
Indicates the current condition, classification, or operational state assigned to a specific geographic or administrative region.
-
D.
countryScope
Indicates that something is limited to, applicable within, or defined at the level of a specific country.
-
E.
countryCurrently
Indicates that an entity is presently located in or associated with a specific country.
- 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_69a88aaba3c48190b351cab9b26989ff |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbf764e348190896af2aeb5520038 |
completed | March 7, 2026, 6:02 a.m. |
| PD | Predicate disambiguation | batch_69abbda52328819089c7ab111bebb0ca |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:46 p.m.