Triple
T6985111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pie Traynor |
E161941
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object |
Pie
Pie is a baked dish typically consisting of a pastry crust filled with sweet or savory ingredients and cooked until golden and set.
|
E633327
|
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: Pie | Statement: [Pie Traynor, nickname, Pie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pie Context triple: [Pie Traynor, nickname, Pie]
-
A.
Cake
"Cake" is a 2014 drama film in which Jennifer Aniston stars as a woman struggling with chronic pain and grief, featuring Mamie Gummer in a supporting role.
-
B.
Pies
The Pies is a common nickname for the Collingwood Football Club, a prominent Australian rules football team in the Australian Football League.
-
C.
PIE
PIE is the three-letter FAA airport code for St. Pete–Clearwater International Airport serving the Tampa Bay area in Florida.
-
D.
PIE
PIE is the commonly used abbreviation for Proto-Indo-European, the hypothetical prehistoric ancestor of most modern European and many South and Central Asian languages.
-
E.
Pie-IX
Pie-IX is a Montreal Metro station in the Mercier–Hochelaga-Maisonneuve borough, serving as a key transit access point to the Olympic Stadium and surrounding attractions.
- 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: Pie Triple: [Pie Traynor, nickname, Pie]
Generated description
Pie is a baked dish typically consisting of a pastry crust filled with sweet or savory ingredients and cooked until golden and set.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Pie Target entity description: Pie is a baked dish typically consisting of a pastry crust filled with sweet or savory ingredients and cooked until golden and set.
-
A.
Cake
"Cake" is a 2014 drama film in which Jennifer Aniston stars as a woman struggling with chronic pain and grief, featuring Mamie Gummer in a supporting role.
-
B.
Pies
The Pies is a common nickname for the Collingwood Football Club, a prominent Australian rules football team in the Australian Football League.
-
C.
PIE
PIE is the three-letter FAA airport code for St. Pete–Clearwater International Airport serving the Tampa Bay area in Florida.
-
D.
PIE
PIE is the commonly used abbreviation for Proto-Indo-European, the hypothetical prehistoric ancestor of most modern European and many South and Central Asian languages.
-
E.
Pie-IX
Pie-IX is a Montreal Metro station in the Mercier–Hochelaga-Maisonneuve borough, serving as a key transit access point to the Olympic Stadium and surrounding attractions.
- 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_69c68855dc0481909b4c7e9e9ed273db |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6db91fbc881908c26b7b991995062 |
completed | March 27, 2026, 7:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c761cb0f1c8190b22b1ad2cd1d7a57 |
completed | March 28, 2026, 5:06 a.m. |
| NEDg | Description generation | batch_69c7630440508190a66f218fd912d732 |
completed | March 28, 2026, 5:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7639747b88190b3429817d53c5703 |
completed | March 28, 2026, 5:13 a.m. |
Created at: March 27, 2026, 2:31 p.m.