Triple
T6500500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Love Story |
E148870
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Romeo |
E54683
|
NE 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: Romeo | Statement: [Love Story, featuresCharacter, Romeo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Romeo Context triple: [Love Story, featuresCharacter, Romeo]
-
A.
Romeo
Romeo is a small statutory town located in Conejos County in southern Colorado, United States.
-
B.
Romeo Montague
chosen
Romeo Montague is the passionate young lover and tragic protagonist of William Shakespeare’s play "Romeo and Juliet," whose forbidden romance ends in mutual death.
-
C.
Lord Capulet
Lord Capulet is Juliet’s authoritative and temperamental father in Shakespeare’s tragedy, whose decisions and conflicts help drive the lovers toward their fatal end.
-
D.
Friar Laurence
Friar Laurence is the well-intentioned Franciscan priest in Shakespeare’s "Romeo and Juliet" who secretly marries the young lovers and devises the ill-fated plan that leads to their tragic end.
-
E.
Juliet Capulet
Juliet Capulet is the young heroine of William Shakespeare’s tragedy "Romeo and Juliet," renowned as one half of literature’s most famous star-crossed lovers.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c687e9ad288190bae5bcac9c8ac855 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c68ad2e148819088be5c48ad73dc59 |
completed | March 27, 2026, 1:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6cb26d2d08190a52084c3a8c0d8f8 |
completed | March 27, 2026, 6:23 p.m. |
Created at: March 27, 2026, 1:42 p.m.