Triple
T13603747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Concord Pavilion |
E325006
|
entity |
| Predicate | architect |
P184
|
FINISHED |
| Object |
Peter Dodge
Peter Dodge is an architect best known for designing the Concord Pavilion, a prominent outdoor concert venue in Concord, California.
|
E1050070
|
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: Peter Dodge | Statement: [Concord Pavilion, architect, Peter Dodge]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Dodge Context triple: [Concord Pavilion, architect, Peter Dodge]
-
A.
Matt Dodge
Matt Dodge is a former NFL punter best known for his time with the New York Giants, particularly for a pivotal misplayed punt in a 2010 game against the Philadelphia Eagles.
-
B.
Peter Chase
Peter Chase is a composer known for creating the musical score for the film "L'Appartement."
-
C.
Jack Deerson
Jack Deerson is a cinematographer best known for his work on the 1971 road movie "Two-Lane Blacktop."
-
D.
Peter Stone
Peter Stone is an American computer scientist known for his influential work in artificial intelligence and robotics, particularly in multiagent systems and robot soccer.
-
E.
Peter Stone
Peter Stone was an American screenwriter and playwright best known for crafting witty, sophisticated scripts for films such as "Charade" and the musical "1776."
- 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: Peter Dodge Triple: [Concord Pavilion, architect, Peter Dodge]
Generated description
Peter Dodge is an architect best known for designing the Concord Pavilion, a prominent outdoor concert venue in Concord, California.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Peter Dodge Target entity description: Peter Dodge is an architect best known for designing the Concord Pavilion, a prominent outdoor concert venue in Concord, California.
-
A.
Matt Dodge
Matt Dodge is a former NFL punter best known for his time with the New York Giants, particularly for a pivotal misplayed punt in a 2010 game against the Philadelphia Eagles.
-
B.
Peter Chase
Peter Chase is a composer known for creating the musical score for the film "L'Appartement."
-
C.
Jack Deerson
Jack Deerson is a cinematographer best known for his work on the 1971 road movie "Two-Lane Blacktop."
-
D.
Peter Stone
Peter Stone is an American computer scientist known for his influential work in artificial intelligence and robotics, particularly in multiagent systems and robot soccer.
-
E.
Peter Stone
Peter Stone was an American screenwriter and playwright best known for crafting witty, sophisticated scripts for films such as "Charade" and the musical "1776."
- 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_69d80769eaf081909d82f44e484d6113 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb07ca07481909c45da551ea61ab4 |
completed | April 12, 2026, 2:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f77f93ec588190993baec788d22670 |
completed | May 3, 2026, 5:02 p.m. |
| NEDg | Description generation | batch_69f780bc40f481908191fec9a563e547 |
completed | May 3, 2026, 5:07 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7817b8c408190b7211ba8fd892f75 |
completed | May 3, 2026, 5:10 p.m. |
Created at: April 9, 2026, 9:49 p.m.