Triple
T2088636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moore |
E32614
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Muir |
E99938
|
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: Muir | Statement: [Moore, hasVariant, Muir]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Muir Context triple: [Moore, hasVariant, Muir]
-
A.
Muir
chosen
Muir is a Scottish surname most famously associated with naturalist and conservationist John Muir.
-
B.
MacKenzie
MacKenzie is the first name of MacKenzie Scott, the American novelist and philanthropist known for her large-scale charitable giving.
-
C.
Issaquah
Issaquah is a small city in Washington State known for its scenic setting between the Issaquah Alps, outdoor recreation opportunities, and historic downtown.
-
D.
Mount Dana
Mount Dana is a prominent high-elevation peak on the eastern edge of Yosemite National Park in California’s Sierra Nevada, known for its sweeping alpine views and relatively accessible summit hike.
-
E.
Grizzly Bay
Grizzly Bay is a shallow tidal embayment in Northern California that forms part of the greater San Francisco Bay–Delta estuarine system.
- 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_69a885eba0708190999696a45cbec816 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abba712388819091d68a4bb99f6b17 |
completed | March 7, 2026, 5:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae2742834c8190ad9be71128959e0c |
completed | March 9, 2026, 1:49 a.m. |
Created at: March 4, 2026, 7:43 p.m.