Triple
T38209724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LEH |
E1010504
|
entity |
| Predicate | associatedCompanyShortName |
P178991
|
FINISHED |
| Object | Lehman Brothers |
E309477
|
NE FINISHED |
How this triple was built (2 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: Lehman Brothers | Statement: [LEH, associatedCompanyShortName, Lehman Brothers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedCompanyShortName Context triple: [LEH, associatedCompanyShortName, Lehman Brothers]
-
A.
associatedCompanyCommonName
chosen
Indicates that there is a relationship where a company is linked to a commonly used or publicly recognized version of its name.
-
B.
associatedCompanyKnownFor
Indicates that a company linked to an entity is recognized or notable for a particular product, service, activity, or characteristic.
-
C.
associatedCompanyGlobalScope
Indicates that there is a relationship linking an entity to a company at a global (worldwide) organizational scope.
-
D.
associatedCompanyFoundedAs
Indicates that one company was originally established or created under a former name or organizational form that is now associated with the current company.
-
E.
relatedCompanyType
Indicates the type or nature of the relationship that one company has to another company.
- F. None of above.
Provenance (4 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_69f76dcdc7708190a5f1751d53f40ffe |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a41b28879d88190b5f6b5489f46bc6b |
completed | June 28, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_6a037a1c850c819088795a7ae59bdeb8 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:30 p.m.