Triple
T37113829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MBMC |
E919064
|
entity |
| Predicate | hasAdministrativeWing |
P196765
|
FINISHED |
| Object | Yes |
—
|
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: Yes | Statement: [MBMC, hasAdministrativeWing, Yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAdministrativeWing Context triple: [MBMC, hasAdministrativeWing, Yes]
-
A.
hasAdministrativeEquivalent
Indicates that two entities hold equivalent roles, powers, or status within an administrative or governance structure.
-
B.
hasFictionalAdministration
Indicates that an entity is governed, managed, or overseen by an administration that is fictional rather than real.
-
C.
hasAdministrativeType
Indicates that an entity is associated with a specific category or level of administrative classification (such as type of jurisdiction or administrative unit).
-
D.
hasWingRole
Indicates that an entity holds a specific role or position within a wing or sub-unit of a larger organization or structure.
-
E.
hasAdministrativeSignificance
Indicates that something holds official importance, authority, or relevance within an administrative or governmental context.
- 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_69f76e9c57148190ba789dd059645bb9 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fe6739d4dc8190ae7505c089bbac29 |
completed | May 8, 2026, 10:44 p.m. |
| PD | Predicate disambiguation | batch_69fe6541dffc81909c66a61ba69f38fc |
completed | May 8, 2026, 10:35 p.m. |
| PDg | Predicate description generation | batch_69fe673905408190a2ae68c2c9563403 |
completed | May 8, 2026, 10:44 p.m. |
Created at: May 3, 2026, 4:15 p.m.