Triple
T29205751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | the Milano |
E740406
|
entity |
| Predicate | hasHangarLocation |
P22186
|
FINISHED |
| Object | Knowhere (various points in the MCU) |
—
|
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: Knowhere (various points in the MCU) | Statement: [the Milano, hasHangarLocation, Knowhere (various points in the MCU)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHangarLocation Context triple: [the Milano, hasHangarLocation, Knowhere (various points in the MCU)]
-
A.
hasHangarCount
Indicates the number of hangars associated with or contained by an entity.
-
B.
hasHangars
chosen
Indicates that one entity possesses or contains hangars used for housing aircraft or similar vehicles.
-
C.
hangarType
Indicates the specific category or type of hangar associated with an entity.
-
D.
hasBlueImpulseHangar
Indicates that an entity possesses or is associated with a blue-colored hangar designated for impulse-related operations or storage.
-
E.
hasHeliport
Indicates that an entity possesses or is equipped with a heliport facility for helicopter landing and takeoff.
- 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_69f07cb974108190b7e86ca489a6ebb6 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f67f7efc3c8190986d2d95b7a23729 |
completed | May 2, 2026, 10:49 p.m. |
| PD | Predicate disambiguation | batch_69f67e40af9881908de3a4aa15f70a83 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 28, 2026, 12:09 p.m.