Triple
T24111743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bella Baxter |
E597394
|
entity |
| Predicate | relationshipTypeWith Archibald McCandless |
P155099
|
FINISHED |
| Object | romantic partner in the novel |
—
|
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 partner in the novel | Statement: [Bella Baxter, relationshipTypeWith Archibald McCandless, romantic partner in the novel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWith Archibald McCandless Context triple: [Bella Baxter, relationshipTypeWith Archibald McCandless, romantic partner in the novel]
-
A.
relationshipTypeWith Jim Burden
Indicates the specific nature or category of relationship that an entity has with Jim Burden.
-
B.
relationshipToMarkWatney
Indicates the specific type of personal or social relationship an entity has with Mark Watney.
-
C.
relationshipToAddieBundren
Indicates the specific familial, social, or emotional relationship that one entity has to Addie Bundren.
-
D.
relationshipTypeWithKatnissEverdeen
Indicates the type or nature of the relationship an entity has with Katniss Everdeen.
-
E.
relationshipTypeWith Sebastian Wilder
Indicates the specific nature or category of relationship that an entity has with Sebastian Wilder.
- 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_69e288c60f9c8190af948d7354aedbeb |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1de1bd81c8190a44f07487d2ba176 |
completed | April 29, 2026, 10:31 a.m. |
| PD | Predicate disambiguation | batch_69f17651458c8190bbfd301883e46085 |
completed | April 29, 2026, 3:09 a.m. |
| PDg | Predicate description generation | batch_69f17b58012c81909106b332db399023 |
completed | April 29, 2026, 3:30 a.m. |
Created at: April 17, 2026, 11:03 p.m.