Triple
T6218670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arnot Mall |
E139054
|
entity |
| Predicate | hasFormerAnchorTenant |
P18036
|
FINISHED |
| Object |
Bradlees
Bradlees was a now-defunct American discount department store chain that operated primarily in the Northeastern United States.
|
E578665
|
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: Bradlees | Statement: [Arnot Mall, hasFormerAnchorTenant, Bradlees]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bradlees Context triple: [Arnot Mall, hasFormerAnchorTenant, Bradlees]
-
A.
Bradley
Bradley is a locality in England historically associated with the life and death of the pioneering ironmaster John Wilkinson.
-
B.
Bradley
Bradley is the given first name of Brad Stevens, an American professional basketball executive and former head coach of the Boston Celtics.
-
C.
Bradley
Bradley is a common English surname borne by numerous notable individuals across sports, politics, entertainment, and other fields.
-
D.
Bradley
Bradley is a small unincorporated community located in Raleigh County, West Virginia, known primarily as a residential area near the city of Beckley.
-
E.
Ed Bradley
Ed Bradley was an acclaimed American broadcast journalist best known as a pioneering and long-serving correspondent on the CBS news magazine program "60 Minutes."
- 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: Bradlees Triple: [Arnot Mall, hasFormerAnchorTenant, Bradlees]
Generated description
Bradlees was a now-defunct American discount department store chain that operated primarily in the Northeastern United States.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bradlees Target entity description: Bradlees was a now-defunct American discount department store chain that operated primarily in the Northeastern United States.
-
A.
Bradley
Bradley is a locality in England historically associated with the life and death of the pioneering ironmaster John Wilkinson.
-
B.
Bradley
Bradley is the given first name of Brad Stevens, an American professional basketball executive and former head coach of the Boston Celtics.
-
C.
Bradley
Bradley is a common English surname borne by numerous notable individuals across sports, politics, entertainment, and other fields.
-
D.
Bradley
Bradley is a small unincorporated community located in Raleigh County, West Virginia, known primarily as a residential area near the city of Beckley.
-
E.
Ed Bradley
Ed Bradley was an acclaimed American broadcast journalist best known as a pioneering and long-serving correspondent on the CBS news magazine program "60 Minutes."
- 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_69c008aecb0c81909984b48f733ce8ae |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062a481908190a1418d9fcfaf8137 |
completed | March 22, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c20dbbacf08190bbbb2863e19c3e7c |
completed | March 24, 2026, 4:06 a.m. |
| NEDg | Description generation | batch_69c214980bbc8190b188b3c821ea13ea |
completed | March 24, 2026, 4:35 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c2157d43048190a0376cdc9024c5f9 |
completed | March 24, 2026, 4:39 a.m. |
Created at: March 22, 2026, 4:21 p.m.