Triple
T14956739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metro Man |
E372950
|
entity |
| Predicate | cityProtected |
P55965
|
FINISHED |
| Object | Metro City |
E372951
|
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: Metro City | Statement: [Metro Man, cityProtected, Metro City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Metro City Context triple: [Metro Man, cityProtected, Metro City]
-
A.
Metro City
chosen
Metro City is the fictional, superhero-populated metropolis that serves as the primary setting of the animated film "Megamind."
-
B.
Metro City
Metro City is a fictional, crime-ridden American metropolis featured as the primary location in Capcom’s beat ’em up video game series Final Fight.
-
C.
Metroville
Metroville is the fictional, modern American city that serves as the primary urban setting for Pixar’s superhero film "The Incredibles."
-
D.
Spring City
Spring City is the popular nickname of Kunming, the capital of Yunnan Province in China, renowned for its mild, spring-like climate year-round.
-
E.
Spring City
Spring City is a nickname for Waukesha, Wisconsin, reflecting its historic abundance of natural springs.
- 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_69d85cca979481908747d2a81eba1cea |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6cc73848190ac181782b20dc838 |
completed | April 15, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe7e9e74fc8190bdd10a25c39829f3 |
completed | May 9, 2026, 12:23 a.m. |
Created at: April 10, 2026, 2:40 a.m.