Triple
T12515186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | COFF |
E299175
|
entity |
| Predicate | influenced |
P9
|
FINISHED |
| Object |
PE format
The PE (Portable Executable) format is the standard file format for executables, object code, and DLLs in 32-bit and 64-bit versions of Windows operating systems.
|
E986427
|
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: PE format | Statement: [COFF, influenced, PE format]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PE format Context triple: [COFF, influenced, PE format]
-
A.
PEG
PEG is the IATA airport code for Perugia San Francesco d’Assisi – Umbria International Airport in central Italy.
-
B.
PEG
PEG is the stock ticker symbol for Public Service Enterprise Group, a major U.S. energy company primarily involved in regulated electric and gas utility operations and power generation.
-
C.
PEG
PEG is a German vehicle registration code assigned to the Bayreuth district region.
-
D.
PICA format
PICA format is a library data exchange and cataloging standard widely used in German-speaking countries, particularly in academic and research libraries.
-
E.
Pe
Pe is a Hebrew consonant letter that represents a "p" or "f" sound and has both standard and final written forms.
- 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: PE format Triple: [COFF, influenced, PE format]
Generated description
The PE (Portable Executable) format is the standard file format for executables, object code, and DLLs in 32-bit and 64-bit versions of Windows operating systems.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: PE format Target entity description: The PE (Portable Executable) format is the standard file format for executables, object code, and DLLs in 32-bit and 64-bit versions of Windows operating systems.
-
A.
PEG
PEG is the IATA airport code for Perugia San Francesco d’Assisi – Umbria International Airport in central Italy.
-
B.
PEG
PEG is the stock ticker symbol for Public Service Enterprise Group, a major U.S. energy company primarily involved in regulated electric and gas utility operations and power generation.
-
C.
PEG
PEG is a German vehicle registration code assigned to the Bayreuth district region.
-
D.
PICA format
PICA format is a library data exchange and cataloging standard widely used in German-speaking countries, particularly in academic and research libraries.
-
E.
Pe
Pe is a Hebrew consonant letter that represents a "p" or "f" sound and has both standard and final written forms.
- 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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9541f80148190976d1d912fe155d0 |
completed | April 10, 2026, 7:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64bbd58b88190baeb99380babf64f |
completed | May 2, 2026, 7:08 p.m. |
| NEDg | Description generation | batch_69f64ce257348190b01179773992d414 |
completed | May 2, 2026, 7:13 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f64db823bc819098152a96db960b10 |
completed | May 2, 2026, 7:17 p.m. |
Created at: April 8, 2026, 9:57 p.m.