Triple
T11997116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lord Montague |
E285559
|
entity |
| Predicate | child |
P120
|
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: [Lord Montague, child, Romeo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Romeo Context triple: [Lord Montague, child, Romeo]
-
A.
Romeo
Romeo is a small statutory town located in Conejos County in southern Colorado, United States.
-
B.
Romeo
Romeo is a recurring mad-scientist villain in the children's animated superhero series PJ Masks, known for his inventive gadgets and schemes to outsmart the heroes.
-
C.
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.
-
D.
Giulietta
Giulietta is the given name of Countess Giulietta Guicciardi, an aristocratic woman best known as one of Ludwig van Beethoven’s piano students and the dedicatee of his "Moonlight" Sonata.
-
E.
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.
- 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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903c172788190b92042e9d10a48bf |
completed | April 10, 2026, 2:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f49d183ee881908f1c0ca4562344a9 |
completed | May 1, 2026, 12:31 p.m. |
Created at: April 8, 2026, 9:46 p.m.