Triple
T5220133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Western Montana |
E117849
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Libby |
E504088
|
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: Libby | Statement: [Western Montana, hasCity, Libby]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Libby Context triple: [Western Montana, hasCity, Libby]
-
A.
Libby
Libby is a surname most notably associated with Willard F. Libby, the American chemist who developed radiocarbon dating and won the Nobel Prize in Chemistry.
-
B.
Libby
chosen
Libby is a small city in northwestern Montana known for its scenic setting near the Kootenai River and surrounding forests and mountains.
-
C.
Lila
Lila is a central female character in Max Frisch’s novel "Mein Name sei Gantenbein," around whom the narrator constructs one of his imagined lives and relationships.
-
D.
Zoe
Zoe is a feminine given name of Greek origin meaning "life," commonly used in many English-speaking and European countries.
-
E.
Maddy
Maddy is a common diminutive or nickname typically used for the given name Madison.
- 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_69bd4465e03081909bfcfd7113062590 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7ab846548190bcd2c5cd238f6cd9 |
completed | March 20, 2026, 4:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bef8059c808190aac709a199541ce7 |
completed | March 21, 2026, 7:56 p.m. |
Created at: March 20, 2026, 1:48 p.m.