Triple
T10162753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Villahermosa |
E233929
|
entity |
| Predicate | populationRankInTabasco |
P92362
|
FINISHED |
| Object | largest city |
—
|
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: largest city | Statement: [Villahermosa, populationRankInTabasco, largest city]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: populationRankInTabasco Context triple: [Villahermosa, populationRankInTabasco, largest city]
-
A.
populationRankInMexico
Indicates the relative position of an entity in terms of population size compared to other entities within Mexico.
-
B.
populationRankInTexas
Indicates the relative position of an entity in terms of population size compared to other entities within Texas.
-
C.
populationRankInPuertoRico
Indicates the relative position of a place in terms of population size compared to other places within Puerto Rico.
-
D.
populationRankInVenezuela
Indicates the relative position of an entity in terms of population size compared to other entities within Venezuela.
-
E.
provinceRank
Indicates the relative position or level assigned to a province within an ordered ranking or hierarchy.
- 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_69ca848e80748190b91d1e04d35512c7 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cdec5b5194819095645e9174897b0f |
completed | April 2, 2026, 4:11 a.m. |
| PD | Predicate disambiguation | batch_69cd4ba795808190acc9124c98c6e40f |
completed | April 1, 2026, 4:45 p.m. |
| PDg | Predicate description generation | batch_69cd4f8f869c8190a82ad040993e0244 |
completed | April 1, 2026, 5:02 p.m. |
Created at: March 30, 2026, 9:09 p.m.