Triple
T16230494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loomis |
E393965
|
entity |
| Predicate | formerName |
P65
|
FINISHED |
| Object | Placer |
E393965
|
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: Placer | Statement: [Loomis, formerName, Placer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Placer Context triple: [Loomis, formerName, Placer]
-
A.
Placer
chosen
Placer is the former historic name of the town now known as Loomis in Placer County, California.
-
B.
Placer
Placer is a coastal municipality in the province of Masbate in the Philippines, known for its fishing communities and rural island setting.
-
C.
The Gold Town
The Gold Town is a nickname for Skellefteå, a Swedish city historically associated with gold mining and rich mineral resources.
-
D.
Sutter’s Gold
Sutter’s Gold is a historical novel by Blaise Cendrars that fictionalizes the life and downfall of John Sutter during the California Gold Rush.
-
E.
Gold Mine Town
Gold Mine Town is a themed attraction area in Shenzhen’s Happy Valley amusement park designed to resemble a historic gold-mining frontier town.
- 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_69d87f204df88190a8f88923decf9835 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e23d29438c81909aa2724cc47bb959 |
completed | April 17, 2026, 2:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0007a0ab08819082aea4c312c9ffc7 |
completed | May 10, 2026, 4:20 a.m. |
Created at: April 10, 2026, 5:03 a.m.