Triple
T23394152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Esterline Technologies |
E594102
|
entity |
| Predicate | tickerSymbol |
P1447
|
FINISHED |
| Object |
ESL
ESL is the stock ticker symbol for Esterline Technologies, a former aerospace and defense manufacturing company.
|
E1582494
|
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: ESL | Statement: [Esterline Technologies, tickerSymbol, ESL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ESL Context triple: [Esterline Technologies, tickerSymbol, ESL]
-
A.
ESL
ESL is the National Rail station code assigned to Eastleigh railway station in Hampshire, England.
-
B.
ESL
ESL is a major global esports company known for organizing and hosting professional video game tournaments and leagues worldwide.
-
C.
EFL
EFL is a professional football league system in England that organizes and oversees the three divisions below the Premier League.
-
D.
EFL
EFL (Enlightenment Foundation Libraries) is a collection of open-source graphics and user interface libraries designed for building fast, lightweight, and visually rich applications, particularly on resource-constrained devices.
-
E.
EFL
EFL is the IATA airport code for Kefalonia International Airport on the Greek island of Kefalonia.
- 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: ESL Triple: [Esterline Technologies, tickerSymbol, ESL]
Generated description
ESL is the stock ticker symbol for Esterline Technologies, a former aerospace and defense manufacturing company.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: ESL Target entity description: ESL is the stock ticker symbol for Esterline Technologies, a former aerospace and defense manufacturing company.
-
A.
ESL
ESL is a major global esports company known for organizing and hosting professional video game tournaments and leagues worldwide.
-
B.
ESL
ESL is the National Rail station code assigned to Eastleigh railway station in Hampshire, England.
-
C.
EFL
EFL is a professional football league system in England that organizes and oversees the three divisions below the Premier League.
-
D.
EFL
EFL (Enlightenment Foundation Libraries) is a collection of open-source graphics and user interface libraries designed for building fast, lightweight, and visually rich applications, particularly on resource-constrained devices.
-
E.
EFL
EFL is the IATA airport code for Kefalonia International Airport on the Greek island of Kefalonia.
- 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_69e25d2754fc819085deea939bde60ab |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a49eb3b881909da7f1c47c67c81f |
completed | April 29, 2026, 6:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c5dedc3548190b7340fa46db37737 |
completed | May 19, 2026, 12:56 p.m. |
| NEDg | Description generation | batch_6a0c5eb51fe08190a2f12988d03e7fb8 |
completed | May 19, 2026, 12:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0c5f58dd448190bdf6674d65098c3f |
completed | May 19, 2026, 1:02 p.m. |
Created at: April 17, 2026, 5:36 p.m.