Triple
T37888243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sally Seton |
E945055
|
entity |
| Predicate | relationshipToClarissaDalloway |
P204451
|
FINISHED |
| Object | close friend in youth |
—
|
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: close friend in youth | Statement: [Sally Seton, relationshipToClarissaDalloway, close friend in youth]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToClarissaDalloway Context triple: [Sally Seton, relationshipToClarissaDalloway, close friend in youth]
-
A.
relationshipToAlgernonMoncrieff
Indicates the specific familial, social, or personal connection that one entity has to Algernon Moncrieff.
-
B.
relationshipToBrionyTallis
Indicates the specific type of personal or social relationship an entity has with Briony Tallis.
-
C.
relationshipToElinorDashwood
Indicates the specific familial, social, or interpersonal connection that one entity has to Elinor Dashwood.
-
D.
relationshipToEmmaWoodhouse
Indicates the specific interpersonal or familial connection that an entity has to Emma Woodhouse.
-
E.
relationshipToNickCharles
Indicates a specified type of personal or social relationship that an entity has with Nick Charles.
- 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_69f76ef02668819089e7940c4001af5e |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037cae084081909004d77514c5f286 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a192a008190a9917688a9e804f4 |
completed | May 12, 2026, 7:06 p.m. |
| PDg | Predicate description generation | batch_6a037c84ecbc81908232e5215355f43b |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:19 p.m.