Triple
T12249247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King Princess |
E291928
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Talia |
E351832
|
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: Talia | Statement: [King Princess, notableWork, Talia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Talia Context triple: [King Princess, notableWork, Talia]
-
A.
Talia
chosen
Talia is a feminine given name used in various cultures, often associated with meanings like “dew from heaven” or “to bloom.”
-
B.
Lyla
"Lyla" is a song by the English rock band Oasis, featured on their 2005 album "Don't Believe the Truth."
-
C.
Tessa
Tessa is a feminine given name commonly used in English-speaking countries, often as a diminutive of Theresa or Therese.
-
D.
Talita
Talita is a central character in Julio Cortázar’s novel "Rayuela" ("Hopscotch"), known for her enigmatic presence and complex relationships within the bohemian Parisian and Buenos Aires circles depicted in the story.
-
E.
Zaira
Zaira is an 1829 opera in two acts by Italian composer Vincenzo Bellini, known for its bel canto style and dramatic vocal writing.
- 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_69d6ab67950c8190be08450a06228c4b |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91cc50d808190a3c8d1ada31a6a91 |
completed | April 10, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f61e620ed88190b46d256ebe994714 |
completed | May 2, 2026, 3:55 p.m. |
Created at: April 8, 2026, 9:52 p.m.