Triple
T13001163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chloe Frazer |
E322171
|
entity |
| Predicate | relationshipTypeWithNathanDrake |
P38921
|
FINISHED |
| Object | former romantic partner |
—
|
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: former romantic partner | Statement: [Chloe Frazer, relationshipTypeWithNathanDrake, former romantic partner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithNathanDrake Context triple: [Chloe Frazer, relationshipTypeWithNathanDrake, former romantic partner]
-
A.
relationshipToCharacter
chosen
Indicates the specific type of personal, social, or narrative connection that one entity has to a given character.
-
B.
relationshipTypeWithJakeBarnes
Indicates the specific nature or category of relationship that an entity has with Jake Barnes.
-
C.
relationshipStatusWithJackSparrow
Indicates the type or state of a subject’s personal relationship with Jack Sparrow.
-
D.
relationshipTypeWithRobertCohn
Indicates the specific nature or category of relationship that an entity has with Robert Cohn.
-
E.
playerRelations
Indicates the nature or status of the relationship between players, such as alliances, rivalries, or other interpersonal dynamics.
- 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_69d807657e8c8190bd9435ee2f823845 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e9828748190b2ad9ea29180b7d3 |
completed | April 10, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69d97dc153a081909d13a694993f074a |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 8:47 p.m.