Triple
T9727165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manuela Testolini |
E235642
|
entity |
| Predicate | marriageToEricBenétStart |
P90687
|
FINISHED |
| Object | 2011 |
—
|
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: 2011 | Statement: [Manuela Testolini, marriageToEricBenétStart, 2011]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriageToEricBenétStart Context triple: [Manuela Testolini, marriageToEricBenétStart, 2011]
-
A.
marriageStartWithBenAffleck
Indicates the point in time when a marriage involving Ben Affleck begins.
-
B.
spouseOfSince
Indicates that two individuals are spouses and specifies the date or time from which their marital relationship has been in effect.
-
C.
marriageToJoelMcAndrewStart
Indicates the time or event when an entity’s marriage to Joel McAndrew begins.
-
D.
marriedToBeforeFameOf
Indicates that one person was married to another person before the latter became famous.
-
E.
metSpouseAt
Indicates that one person first encountered or became acquainted with their spouse at a particular place, event, or time.
- 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_69ca84d0fad481909cdd45aa77416c48 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9e7af544819090a8a1adec41943c |
completed | April 1, 2026, 10:38 p.m. |
| PD | Predicate disambiguation | batch_69cd03c6ffc88190a5e9569e19122ad5 |
completed | April 1, 2026, 11:38 a.m. |
| PDg | Predicate description generation | batch_69cd07c5c978819084abc7267a5ced80 |
completed | April 1, 2026, 11:55 a.m. |
Created at: March 30, 2026, 8:21 p.m.