Triple
T801158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ciudad Serdán |
E17129
|
entity |
| Predicate | postalAddressCountry |
P17984
|
FINISHED |
| Object | MX |
—
|
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: MX | Statement: [Ciudad Serdán, postalAddressCountry, MX]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: postalAddressCountry Context triple: [Ciudad Serdán, postalAddressCountry, MX]
-
A.
hasPostalCountryCode
chosen
Indicates that an entity is associated with a specific country code used for postal addressing or mail routing.
-
B.
postalCounty
Indicates the county associated with an entity for postal addressing or mail delivery purposes.
-
C.
residenceCountry
Indicates the country in which an entity lives or has their primary place of residence.
-
D.
countryOrTerritory
Indicates that one entity is a country or territory associated with, or characterized by, another entity.
-
E.
associatedCountryMostProminently
Indicates the country with which an entity is most strongly or prominently associated, relative to any other countries it may be linked to.
- 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_69a49378b9c48190adbf5f62e5b7aca1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a7cc75e88190bd35aabe51051b51 |
completed | March 1, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69a4a5133bf88190a613e96d1f7cffa7 |
completed | March 1, 2026, 8:44 p.m. |
Created at: March 1, 2026, 7:38 p.m.