Triple
T7478150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Argentine flag |
E176681
|
entity |
| Predicate | isFlownOn |
P76485
|
FINISHED |
| Object | public buildings in Argentina |
—
|
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: public buildings in Argentina | Statement: [Argentine flag, isFlownOn, public buildings in Argentina]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isFlownOn Context triple: [Argentine flag, isFlownOn, public buildings in Argentina]
-
A.
flownWhen
Indicates that one entity has been flown or transported at a specific time or under certain temporal conditions associated with another entity.
-
B.
performedFlightTo
Indicates that an entity (such as an aircraft or airline) carried out a flight whose destination was a specified location.
-
C.
flownAt
Indicates that an entity has traveled or been transported by air at a specified time, place, or condition.
-
D.
flownOn
Indicates that an entity has traveled as a passenger or crew member on a particular flight or aircraft.
-
E.
usedForPassengerFlights
Indicates that something serves as a means or facility for transporting passengers on flights.
- 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_69c69f236ce08190a04d7679f03b29b2 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f4f0088c8190880770ac31e5b7a7 |
completed | March 27, 2026, 9:21 p.m. |
| PD | Predicate disambiguation | batch_69c6f03d967081908a8e696ff9693b90 |
completed | March 27, 2026, 9:01 p.m. |
| PDg | Predicate description generation | batch_69c6f105e320819091db3cdb1f1351f0 |
completed | March 27, 2026, 9:05 p.m. |
Created at: March 27, 2026, 3:42 p.m.