Triple
T673789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lucent Technologies |
E13034
|
entity |
| Predicate | tickerSymbol |
P1447
|
FINISHED |
| Object | LU |
E7866
|
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: LU | Statement: [Lucent Technologies, tickerSymbol, LU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LU Context triple: [Lucent Technologies, tickerSymbol, LU]
-
A.
LU
chosen
LU is the two-letter ISO 3166-1 alpha-2 country code assigned to Luxembourg for international identification and data standards.
-
B.
UL
UL is the vehicle registration code used on license plates for the city of Ulm in Germany.
-
C.
Le
Le is a common Vietnamese surname shared by many notable figures in the country’s history and culture.
-
D.
UB
UB was the common abbreviation for the Urząd Bezpieczeństwa, the communist-era Polish secret police and security service notorious for political repression after World War II.
-
E.
BU
BU is a major private research university in Boston, Massachusetts, known for its diverse academic programs and global student body.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a4933d3bf88190972041cd8cf143b9 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a02537d08190942ee5fc8c50610a |
completed | March 1, 2026, 8:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a5c39f3e1481908f395cdb19cfd2fc |
completed | March 2, 2026, 5:06 p.m. |
Created at: March 1, 2026, 7:36 p.m.