Triple
T33701461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sybil Birling |
E863464
|
entity |
| Predicate | relationshipToEvaSmith |
P156141
|
FINISHED |
| Object | charity applicant she refused |
—
|
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: charity applicant she refused | Statement: [Sybil Birling, relationshipToEvaSmith, charity applicant she refused]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToEvaSmith Context triple: [Sybil Birling, relationshipToEvaSmith, charity applicant she refused]
-
A.
relationshipToEva
chosen
Indicates a specified type of personal or social relationship that an entity has with Eva.
-
B.
relationshipToEleanorVance
Indicates the specific nature or type of relationship an entity has with Eleanor Vance.
-
C.
relationshipToJoeCinque
Indicates a specified type of relationship or connection that an entity has to Joe Cinque.
-
D.
relationshipToDrWatson
Indicates the specific personal or professional relationship an entity has with Dr. Watson.
-
E.
relationshipToJaneRizzoli
Indicates the specific familial, social, or professional relationship that one entity has to Jane Rizzoli.
- 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_69f3498723a08190ac034339cc78eade |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037e0953908190b2930b3c06a40129 |
completed | May 12, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_6a0379f6c3308190b954f7810214ceed |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:43 a.m.