Triple
T19276096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Town of Colma |
E482057
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | City of Souls |
—
|
NE NERFINISHED |
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 Souls | Statement: [Town of Colma, nickname, City of Souls]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: City of Souls Context triple: [Town of Colma, nickname, City of Souls]
-
A.
City of Souls
chosen
City of Souls is the somber nickname for Colma, California, a small town famous for its vast cemeteries and far larger population of the dead than the living.
-
B.
City of Ghosts
City of Ghosts is a 2002 neo-noir crime drama film set largely in Cambodia, following a con man entangled in a dangerous underworld scheme.
-
C.
Library of Souls
Library of Souls is a dark fantasy novel by Ransom Riggs that continues the story of peculiar children as they confront sinister forces in a richly atmospheric, time-bending world.
-
D.
All Souls
All Souls is a Christian feast day commemorating the faithful departed, particularly observed in Western churches on November 2.
-
E.
All Souls
All Souls is a short-lived supernatural drama television series centered on eerie occurrences at a haunted Boston hospital.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8ce54cc8190998418ff1f66ef28 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fbbbdf3481909abb46c71f64106a |
completed | April 20, 2026, 10:11 a.m. |
Created at: April 10, 2026, 1:29 p.m.