Triple
T18823825
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anson Mount |
E460331
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Mount |
E460331
|
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: Mount | Statement: [Anson Mount, familyName, Mount]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mount Context triple: [Anson Mount, familyName, Mount]
-
A.
Mount
chosen
Mount is the surname of American actor Anson Mount, known for his roles in television series such as "Hell on Wheels" and "Star Trek: Discovery."
-
B.
Mountain
Mountain is the nickname of Harlan "Mountain" McClintock, a character from the television series The Twilight Zone.
-
C.
Montagne
Montagne was a prominent French ship of the line that served as the flagship of the French fleet during the late 18th century.
-
D.
The Mount
The Mount is the commonly used nickname for Mount St. Mary's University, a Catholic liberal arts institution located near Emmitsburg, Maryland.
-
E.
The Mount
The Mount is the English name for Surah At-Tur, a chapter of the Qur’an that emphasizes God’s power, the reality of resurrection, and the fate of believers and disbelievers.
- 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_69d8dcf94c288190a06dea029ae4b223 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5a6bce5588190bd0aefcd0c51edad |
completed | April 20, 2026, 4:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a055bcea4fc8190bc9b9e23b1925b6f |
completed | May 14, 2026, 5:21 a.m. |
Created at: April 10, 2026, 11:56 a.m.