Triple
T13146033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Midori |
E312335
|
entity |
| Predicate | relationshipTypeWithToruWatanabe |
P108766
|
FINISHED |
| Object | romantic tension |
—
|
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: romantic tension | Statement: [Midori, relationshipTypeWithToruWatanabe, romantic tension]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithToruWatanabe Context triple: [Midori, relationshipTypeWithToruWatanabe, romantic tension]
-
A.
relationshipToTinaBordereau
Indicates the specific type of personal or professional relationship an entity has with Tina Bordereau.
-
B.
relationshipToTopa
Indicates a familial or social relationship that an entity has specifically with Topa.
-
C.
relationshipTypeWith Suzie Wong
Indicates the specific nature or category of relationship that an entity has with Suzie Wong.
-
D.
relationshipTypeWith Sebastian Wilder
Indicates the specific nature or category of relationship that an entity has with Sebastian Wilder.
-
E.
hasRelationshipTypeWith Tai Frasier
Indicates that there exists a specific type of relationship between an entity and Tai Frasier.
- 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_69d806aabde48190899e13e41659cae5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf054f88190b05ced98d5a22a62 |
completed | April 10, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69d98bbd1d088190b7c69f37fc6eeb64 |
completed | April 10, 2026, 11:46 p.m. |
| PDg | Predicate description generation | batch_69d98ceeb22c8190a6be666031d9e5a4 |
completed | April 10, 2026, 11:51 p.m. |
Created at: April 9, 2026, 9:10 p.m.