Triple
T16417333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brandon Weeden |
E398723
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Weeden
Weeden is a surname most notably associated with Brandon Weeden, an American football quarterback who played in the NFL.
|
E1211166
|
NE FINISHED |
How this triple was built (4 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: Weeden | Statement: [Brandon Weeden, familyName, Weeden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Weeden Context triple: [Brandon Weeden, familyName, Weeden]
-
A.
De Wood
De Wood is a specific variant or form of wood distinguished from the general category of wood materials.
-
B.
Katwoude
Katwoude is a small village in the Dutch province of North Holland, known for its rural polder landscape and traditional farms near the town of Volendam.
-
C.
Woodruff
Woodruff is a small city in northwestern South Carolina known for its historic downtown and location within Spartanburg County.
-
D.
Woodruff
Woodruff is a surname most prominently associated with Judy Woodruff, a longtime American broadcast journalist and former anchor of the PBS NewsHour.
-
E.
Tanne
Tanne is a small village in the Harz region of central Germany, now part of the town of Oberharz am Brocken.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Weeden Triple: [Brandon Weeden, familyName, Weeden]
Generated description
Weeden is a surname most notably associated with Brandon Weeden, an American football quarterback who played in the NFL.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Weeden Target entity description: Weeden is a surname most notably associated with Brandon Weeden, an American football quarterback who played in the NFL.
-
A.
De Wood
De Wood is a specific variant or form of wood distinguished from the general category of wood materials.
-
B.
Katwoude
Katwoude is a small village in the Dutch province of North Holland, known for its rural polder landscape and traditional farms near the town of Volendam.
-
C.
Woodruff
Woodruff is a small city in northwestern South Carolina known for its historic downtown and location within Spartanburg County.
-
D.
Woodruff
Woodruff is a surname most prominently associated with Judy Woodruff, a longtime American broadcast journalist and former anchor of the PBS NewsHour.
-
E.
Tanne
Tanne is a small village in the Harz region of central Germany, now part of the town of Oberharz am Brocken.
- F. None of above. chosen
Provenance (5 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_69d87f2b9024819085c20e52de95d583 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e328798a488190a5fad01c3c95584c |
completed | April 18, 2026, 6:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a003c6ca1bc8190a6c4f675ec8e3a53 |
completed | May 10, 2026, 8:06 a.m. |
| NEDg | Description generation | batch_6a003e3b113c819083e1abc512631e2b |
completed | May 10, 2026, 8:13 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a003eb888e481908eb4ed77f86cf9f3 |
completed | May 10, 2026, 8:15 a.m. |
Created at: April 10, 2026, 5:09 a.m.