Triple
T27104263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jane Nichols |
E686521
|
entity |
| Predicate | weddingRole |
P161854
|
FINISHED |
| Object | maid of honor |
—
|
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: maid of honor | Statement: [Jane Nichols, weddingRole, maid of honor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: weddingRole Context triple: [Jane Nichols, weddingRole, maid of honor]
-
A.
weddingRole
chosen
Indicates the specific role or function an entity has in the context of a wedding event.
-
B.
associatedWithWeddingOf
Indicates a relationship where something is connected or related to the wedding event of specific individuals.
-
C.
weddingDescribedAs
Indicates that a particular wedding is characterized or portrayed using a specific description or label.
-
D.
bride
Indicates that an entity is a woman who is getting married or has just been married in relation to a wedding event or spouse.
-
E.
weddingStatus
Indicates the current state or condition of an entity’s marriage or wedding (e.g., single, engaged, married, divorced).
- F. None of above.
Provenance (3 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_69ef148accd48190b6ed6e13a15f2a4f |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f623b855ac81909a5c7c286a44ec89 |
completed | May 2, 2026, 4:18 p.m. |
| PD | Predicate disambiguation | batch_69f620e0b37481909a280574decbd443 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 27, 2026, 8:49 a.m.