Triple
T28720702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | maz (macrolanguage) |
E730085
|
entity |
| Predicate | representsLanguagesSpokenIn |
P133827
|
FINISHED |
| Object | Mexico |
—
|
NE NERFINISHED |
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: Mexico | Statement: [maz (macrolanguage), representsLanguagesSpokenIn, Mexico]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: representsLanguagesSpokenIn Context triple: [maz (macrolanguage), representsLanguagesSpokenIn, Mexico]
-
A.
representsLanguagesOf
Indicates that one entity specifies or lists the languages associated with, used by, or characteristic of another entity.
-
B.
includesLanguagesSpokenBy
Indicates that one entity contains or covers the set of languages spoken by another entity.
-
C.
includesLanguagesSpokenAlong
Indicates that something (such as a region, route, or area) encompasses or contains the set of languages spoken along its extent or within its boundaries.
-
D.
languagesSpoken
Indicates that an entity is able to communicate using one or more specified languages.
-
E.
refersToLanguageSpokenIn
chosen
Indicates that one entity designates or mentions the language that is spoken in another entity (such as a place or region).
- 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_69f043e91fe48190b73bcd8e08d433e0 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69fd0b92f42881908cd77e3f058adcc2 |
completed | May 7, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69fd0a3d68d4819094d92040f7c48d7c |
completed | May 7, 2026, 9:55 p.m. |
Created at: April 28, 2026, 5:53 a.m.