Triple
T13922437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Garland |
E334779
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Garland |
E1008504
|
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: Garland | Statement: [Red Garland, familyName, Garland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Garland Context triple: [Red Garland, familyName, Garland]
-
A.
Garland
Garland is a large suburban city in the Dallas–Fort Worth metropolitan area known for its diverse community and mixed residential, commercial, and industrial character.
-
B.
Garland
Garland is a faint dwarf galaxy that is a member of the nearby M81 Group of galaxies.
-
C.
Garland
chosen
Garland is a surname most prominently associated with Merrick Garland, the Chief Justice of the United States.
-
D.
Loudermilk
Loudermilk is a comedy-drama television series about a recovering alcoholic and former music critic with a bad attitude who reluctantly helps others in a support group while struggling with his own issues.
-
E.
Garland Woodard
Garland Woodard is an individual notable enough to be recognized as a namesake or representative bearer of the surname Woodard.
- 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_69d81c5f739081908bc05b2461f54828 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2aa5c1f481908a9d8786872f08fe |
completed | April 14, 2026, 11:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7ce7ecb488190b96f67cad4b91968 |
completed | May 3, 2026, 10:38 p.m. |
Created at: April 9, 2026, 10:16 p.m.