Triple
T23658746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CGTP–IN |
E584379
|
entity |
| Predicate | countryLargestStatus |
P25842
|
FINISHED |
| Object | largest trade union confederation in Portugal |
—
|
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 trade union confederation in Portugal | Statement: [CGTP–IN, countryLargestStatus, largest trade union confederation in Portugal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryLargestStatus Context triple: [CGTP–IN, countryLargestStatus, largest trade union confederation in Portugal]
-
A.
largestInCountry
chosen
Indicates that an entity is the largest of its kind within the specified country.
-
B.
hasLargestCountryByArea
Indicates that, among a set of compared entities, the subject is associated with the country that has the greatest land area.
-
C.
isLargestTerritoryOf
Indicates that one territory is the largest, by area or extent, among all territories belonging to a specified entity.
-
D.
oneOfLargest
Indicates that the subject is among the largest members within a specified group or set, but not necessarily the single largest.
-
E.
modernCountryOfArea
Indicates that a specified area or region is currently located within, or administered by, a particular modern 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_69e248ffc0888190ae23c4731eb8b7ac |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b35ded208190ac54e7880d8f2ff3 |
completed | April 29, 2026, 7:29 a.m. |
| PD | Predicate disambiguation | batch_69f118d7903c8190bb590a71771e93af |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:49 p.m.