Triple
T12234272
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evolution |
E291551
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | “City of the Angels” |
E625660
|
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: “City of the Angels” | Statement: [Evolution, hasPart, “City of the Angels”]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: “City of the Angels” Context triple: [Evolution, hasPart, “City of the Angels”]
-
A.
City of Angels
City of Angels is a 1998 romantic fantasy film starring Nicolas Cage and Meg Ryan, known for its melancholic tone and themes of love, mortality, and sacrifice.
-
B.
City of Angels
City of Angels is a popular nickname for Angeles City in the Philippines, reflecting both its name and its vibrant urban character.
-
C.
City of Angels
chosen
City of Angels is a popular nickname for Los Angeles, highlighting both its Spanish-derived name and its iconic status as a major cultural and entertainment hub.
-
D.
City of Angels
City of Angels is an American medical drama television series set in a Los Angeles hospital, notable for its predominantly African American cast.
-
E.
“Tinsel Town”
“Tinsel Town” is a track by the rapper Seal IV, featured as part of his musical work.
- 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_69d6ab668acc8190963ba424049d6aee |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91ca5a06481908c7c6b715b9f6713 |
completed | April 10, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f61e5e32908190a3c1e75ba336ad89 |
completed | May 2, 2026, 3:55 p.m. |
Created at: April 8, 2026, 9:51 p.m.