Triple
T20837547
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Willy Meehan |
E512998
|
entity |
| Predicate | relationshipToAlvirahMeehan |
P142033
|
FINISHED |
| Object | husband |
—
|
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: husband | Statement: [Willy Meehan, relationshipToAlvirahMeehan, husband]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToAlvirahMeehan Context triple: [Willy Meehan, relationshipToAlvirahMeehan, husband]
-
A.
relationshipToLavinia
Indicates the nature or type of relationship an entity has with Lavinia.
-
B.
relationshipToTinaBordereau
Indicates the specific type of personal or professional relationship an entity has with Tina Bordereau.
-
C.
relationshipToMichelle
Indicates the specific type of relationship or connection that an entity has to Michelle.
-
D.
relationshipToAnnDeever
Indicates the specific interpersonal or familial relationship that an entity has to Ann Deever.
-
E.
relationshipToHarveyCheyneJr
Indicates the specific familial, social, or professional relationship that an entity has to Harvey Cheyne Jr.
- 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_69e0b4cf62a88190bbf92351e9e57259 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c3280a1881909a86d1fe498aee50 |
completed | April 21, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e5c9a1f4f48190aa9fb4ef8f8aea5a |
completed | April 20, 2026, 6:37 a.m. |
| PDg | Predicate description generation | batch_69e5d53c4d6881909b4d0a716fa5ed4a |
completed | April 20, 2026, 7:26 a.m. |
Created at: April 16, 2026, 12:42 p.m.