Triple
T14667917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mimi Gardner Gates |
E344427
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Gates |
E17296
|
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: Gates | Statement: [Mimi Gardner Gates, familyName, Gates]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gates Context triple: [Mimi Gardner Gates, familyName, Gates]
-
A.
Gates
Gates is a small city in western Oregon, United States, located in the Santiam Canyon along the North Santiam River.
-
B.
Gates
chosen
Gates is a common English surname most prominently associated with Microsoft co-founder Bill Gates and his family.
-
C.
Mweka Gate
Mweka Gate is a primary descent and exit point on Mount Kilimanjaro, commonly used by climbers finishing popular summit routes.
-
D.
Gateside
Gateside is a small rural village located within the Angus council area in eastern Scotland.
-
E.
The Gates
The Gates is a supernatural drama television series centered on a seemingly idyllic gated community inhabited by vampires, werewolves, and other paranormal beings.
- 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_69d822e283fc8190a0e4c235cf880052 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb54dda1c8190bf16d17e26a2bba6 |
completed | April 14, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdd5e9bb2081908515ab6430e9b1c2 |
completed | May 8, 2026, 12:24 p.m. |
Created at: April 10, 2026, 1:27 a.m.