Triple
T19978008
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meyerland |
E493740
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | George Meyer |
—
|
NE NERFINISHED |
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: George Meyer | Statement: [Meyerland, namedAfter, George Meyer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: George Meyer Context triple: [Meyerland, namedAfter, George Meyer]
-
A.
George Meyer
chosen
George Meyer is a real estate developer best known for creating the Meyerland residential neighborhood in Houston, Texas.
-
B.
Guy Farley
Guy Farley is a British film composer known for his work on a variety of feature films, television projects, and commercials.
-
C.
Allen Lanier
Allen Lanier was an American musician best known as a founding keyboardist and guitarist for the rock band Blue Öyster Cult.
-
D.
Daniel Werfel
Daniel Werfel is an American government official who serves as the Commissioner of the Internal Revenue Service (IRS).
-
E.
Charles Martin
Charles Martin is an American novelist best known for his emotionally driven contemporary Christian and inspirational fiction, including the novel that inspired the film "The Mountain Between Us."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da626a67648190af9653832a3aeced |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e65d11108481908241a2a96a795a7d |
completed | April 20, 2026, 5:06 p.m. |
Created at: April 11, 2026, 3:27 p.m.