Triple
T37971670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miko Nakadai |
E947301
|
entity |
| Predicate | partnerAutobot |
P189683
|
FINISHED |
| Object | Bulkhead |
—
|
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: Bulkhead | Statement: [Miko Nakadai, partnerAutobot, Bulkhead]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partnerAutobot Context triple: [Miko Nakadai, partnerAutobot, Bulkhead]
-
A.
cooperationPartner
Indicates that two entities are engaged in a collaborative relationship, working together toward shared goals or mutual benefit.
-
B.
partnerInOrganizationWith
Indicates that two entities are associated as partners within the same organization or organizational context.
-
C.
partnerInteraction
Indicates an interaction or engagement occurring specifically between partners in a relationship or collaboration.
-
D.
partnerNation
Indicates that one entity is recognized as a collaborating or allied nation in relation to another entity.
-
E.
partnerInMission
Indicates that two or more entities collaborate as partners in carrying out the same mission or operation.
- 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_69f76ef7db908190bba6086673a32300 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbc7b78f9481909f4f8fc2e3fdcde1 |
completed | May 6, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69fbbd18c9908190928d274f8731dfa8 |
completed | May 6, 2026, 10:13 p.m. |
| PDg | Predicate description generation | batch_69fbc7b6c2c88190ad4f58980834053c |
completed | May 6, 2026, 10:59 p.m. |
Created at: May 3, 2026, 4:20 p.m.