Triple
T7753528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FDNY Engine 163 |
E175830
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
E163
E163 is a New York City Fire Department engine company that provides firefighting and emergency response services within its assigned area.
|
E685504
|
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: E163 | Statement: [FDNY Engine 163, abbreviation, E163]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: E163 Context triple: [FDNY Engine 163, abbreviation, E163]
-
A.
E134
E134 is a major east–west European highway in Norway that connects the country’s western fjord region with its southeastern areas through several long tunnels and mountain passes.
-
B.
E18
E18 is a major trans-European road that runs from Craigavon in Northern Ireland through Scotland, Norway, Sweden, and Finland to Saint Petersburg in Russia.
-
C.
E1
E1 is a central London postcode district covering parts of areas such as Whitechapel, Stepney, and Spitalfields in the East End.
-
D.
E6
E6 is a major north–south European route running through Norway and Sweden, forming one of Scandinavia’s primary arterial highways.
-
E.
E313
E313 is a major Belgian motorway connecting Antwerp with Liège and serving as a key east–west transport corridor through the Limburg region.
- 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: E163 Triple: [FDNY Engine 163, abbreviation, E163]
Generated description
E163 is a New York City Fire Department engine company that provides firefighting and emergency response services within its assigned area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: E163 Target entity description: E163 is a New York City Fire Department engine company that provides firefighting and emergency response services within its assigned area.
-
A.
E134
E134 is a major east–west European highway in Norway that connects the country’s western fjord region with its southeastern areas through several long tunnels and mountain passes.
-
B.
E18
E18 is a major trans-European road that runs from Craigavon in Northern Ireland through Scotland, Norway, Sweden, and Finland to Saint Petersburg in Russia.
-
C.
E1
E1 is a central London postcode district covering parts of areas such as Whitechapel, Stepney, and Spitalfields in the East End.
-
D.
E6
E6 is a major north–south European route running through Norway and Sweden, forming one of Scandinavia’s primary arterial highways.
-
E.
E313
E313 is a major Belgian motorway connecting Antwerp with Liège and serving as a key east–west transport corridor through the Limburg region.
- 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_69c6996180088190832e38e8d83ff54a |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c703b4b54c819088ffe918ce5c7de4 |
completed | March 27, 2026, 10:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8be5a649c81909c94d629348b34fc |
completed | March 29, 2026, 5:53 a.m. |
| NEDg | Description generation | batch_69c8bf06242c8190b38bae041484096d |
completed | March 29, 2026, 5:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c8bf5aa1348190a5c369bece6fb6db |
completed | March 29, 2026, 5:57 a.m. |
Created at: March 27, 2026, 4:08 p.m.