Triple
T28694033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Armand Goldman |
E729362
|
entity |
| Predicate | relationshipToAlbertGoldman |
P202186
|
FINISHED |
| Object | 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: romantic partner | Statement: [Armand Goldman, relationshipToAlbertGoldman, romantic partner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToAlbertGoldman Context triple: [Armand Goldman, relationshipToAlbertGoldman, romantic partner]
-
A.
relationshipWithAlbertSteptoe
Indicates having some form of personal or familial relationship with Albert Steptoe.
-
B.
relationshipToEmmaGoldman
Indicates the specific type of personal, professional, or ideological relationship an entity has to Emma Goldman.
-
C.
relationshipToAlBundy
Indicates the specific familial, social, or personal relationship that an entity has to the person Al Bundy.
-
D.
relationshipWithAlbertDeMorcerf
Indicates that there exists some form of relationship, connection, or association between an entity and Albert de Morcerf.
-
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_69f043e60b6c8190ac2cd042e77fe6e9 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_6a005e8a2f7c819085bfc6f04b866d87 |
completed | May 10, 2026, 10:31 a.m. |
| PD | Predicate disambiguation | batch_6a005de82ef08190a015b385d1d3443c |
completed | May 10, 2026, 10:28 a.m. |
| PDg | Predicate description generation | batch_6a005e89803c8190ad732ad15affb81f |
completed | May 10, 2026, 10:31 a.m. |
Created at: April 28, 2026, 5:38 a.m.