Triple
T16486759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Our Lady of the Incarnation |
E400464
|
entity |
| Predicate | titleAffirms |
P122969
|
FINISHED |
| Object | Word became flesh in Mary’s womb |
—
|
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: Word became flesh in Mary’s womb | Statement: [Our Lady of the Incarnation, titleAffirms, Word became flesh in Mary’s womb]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleAffirms Context triple: [Our Lady of the Incarnation, titleAffirms, Word became flesh in Mary’s womb]
-
A.
titleRepresents
Indicates that a given title stands for, denotes, or symbolizes a particular concept, role, work, or entity.
-
B.
titles
Indicates that one entity holds a formal title, designation, or name associated with another entity.
-
C.
titleThrough
Indicates a relationship where one entity holds or is identified by a specific title by means of, or via the mediation of, another entity or context.
-
D.
titleImplies
Indicates that holding or being assigned a particular title suggests or entails a certain role, status, or set of responsibilities.
-
E.
title
Indicates that one entity serves as the formal name or designation of another entity.
- 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_69d883813098819084f5409539723b59 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e078d0c8190a5698a5eb9df22d4 |
completed | April 18, 2026, 7:08 a.m. |
| PD | Predicate disambiguation | batch_69e22706b0588190a48a951c5211a617 |
completed | April 17, 2026, 12:26 p.m. |
| PDg | Predicate description generation | batch_69e24556c1348190902a4d116c3137d9 |
completed | April 17, 2026, 2:36 p.m. |
Created at: April 10, 2026, 5:13 a.m.