Triple
T19211604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flextronics International |
E480368
|
entity |
| Predicate | stockTicker |
P1447
|
FINISHED |
| Object |
FLEX
FLEX is a global electronics manufacturing services and supply chain solutions company formerly known as Flextronics International.
|
E1364969
|
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: FLEX | Statement: [Flextronics International, stockTicker, FLEX]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FLEX Context triple: [Flextronics International, stockTicker, FLEX]
-
A.
FLEX
FLEX is a flexible, demand-responsive bus service operated by the North County Transit District in northern San Diego County, California.
-
B.
Flex
Flex is an open-source software development framework originally created by Macromedia for building rich internet applications that run in the Adobe Flash Player.
-
C.
Flex
Flex is a bodybuilding and fitness magazine founded by Joe Weider that focuses on professional bodybuilding, training, and nutrition.
-
D.
flex
flex is a widely used open-source lexical analyzer generator that processes patterns to produce C code for fast text scanning.
-
E.
The Flex Project
The Flex Project is the group responsible for maintaining and developing GNU Flex, a widely used open-source lexical analyzer generator.
- 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: FLEX Triple: [Flextronics International, stockTicker, FLEX]
Generated description
FLEX is a global electronics manufacturing services and supply chain solutions company formerly known as Flextronics International.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: FLEX Target entity description: FLEX is a global electronics manufacturing services and supply chain solutions company formerly known as Flextronics International.
-
A.
FLEX
FLEX is a flexible, demand-responsive bus service operated by the North County Transit District in northern San Diego County, California.
-
B.
Flex
Flex is an open-source software development framework originally created by Macromedia for building rich internet applications that run in the Adobe Flash Player.
-
C.
Flex
Flex is a bodybuilding and fitness magazine founded by Joe Weider that focuses on professional bodybuilding, training, and nutrition.
-
D.
flex
flex is a widely used open-source lexical analyzer generator that processes patterns to produce C code for fast text scanning.
-
E.
The Flex Project
The Flex Project is the group responsible for maintaining and developing GNU Flex, a widely used open-source lexical analyzer generator.
- 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_69d8e8cb8c348190b52075823911c869 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fa365c2481909b3c36ebae18265d |
completed | April 20, 2026, 10:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0700e4e994819080d6767be5e974a3 |
completed | May 15, 2026, 11:17 a.m. |
| NEDg | Description generation | batch_6a07029b7580819090126480b5b1213f |
completed | May 15, 2026, 11:25 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07030deef08190a582bb6f956ef381 |
completed | May 15, 2026, 11:27 a.m. |
Created at: April 10, 2026, 1:21 p.m.