Triple
T7704132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Love & Justice: A Story of Triumph on Two Different Courts |
E174570
|
entity |
| Predicate | titleWord |
P49023
|
FINISHED |
| Object | Love |
—
|
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: Love | Statement: [Love & Justice: A Story of Triumph on Two Different Courts, titleWord, Love]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleWord Context triple: [Love & Justice: A Story of Triumph on Two Different Courts, titleWord, Love]
-
A.
title
Indicates that one entity serves as the formal name or designation of another entity.
-
B.
titlePhrase
Indicates that one entity is a phrase functioning as the title or name of another entity.
-
C.
titleVariant
Indicates that one title is an alternative or variant form of another title referring to the same work or entity.
-
D.
titleRepresents
Indicates that a given title stands for, denotes, or symbolizes a particular concept, role, work, or entity.
-
E.
titleStart
chosen
Indicates that one entity’s title begins with the text or substring represented by the other entity.
- 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_69c6995a72cc8190998e56daa6f8e453 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c70402169481909b219dc5f4a64b9b |
completed | March 27, 2026, 10:26 p.m. |
| PD | Predicate disambiguation | batch_69c70165e78c8190bf6b3c34e243cb81 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:03 p.m.