Triple
T9814995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lacey Pemberton |
E238378
|
entity |
| Predicate | relationshipToQuentinJacobsen |
P90153
|
FINISHED |
| Object | friend and classmate |
—
|
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: friend and classmate | Statement: [Lacey Pemberton, relationshipToQuentinJacobsen, friend and classmate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToQuentinJacobsen Context triple: [Lacey Pemberton, relationshipToQuentinJacobsen, friend and classmate]
-
A.
relationshipToBenjy
Indicates the specific type of relationship or connection an entity has to Benjy.
-
B.
relationshipToJosephCooper
Indicates the specific familial, social, or professional relationship that one entity has to Joseph Cooper.
-
C.
relationshipToEvanHansen
Indicates the type or nature of a person's relationship or connection to Evan Hansen.
-
D.
relationshipToHarveyCheyneJr
Indicates the specific familial, social, or professional relationship that an entity has to Harvey Cheyne Jr.
-
E.
relationshipToGabeGoodman
Indicates the specific type of personal or social relationship an entity has with Gabe Goodman.
- 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_69ca84dfde1481909f47c286d715f892 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb2f19660819083e3f15780352052 |
completed | April 2, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69cd03e01ea881909a7d93fc3994ace5 |
completed | April 1, 2026, 11:39 a.m. |
| PDg | Predicate description generation | batch_69cd06abc9248190a506b64e9c516d03 |
completed | April 1, 2026, 11:51 a.m. |
Created at: March 30, 2026, 8:30 p.m.