Triple
T2416368
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alcatel |
E52311
|
entity |
| Predicate | tickerSymbol |
P1447
|
FINISHED |
| Object |
ALA (historical)
ALA (historical) was the former stock ticker symbol used to represent the French telecommunications company Alcatel on securities exchanges.
|
E264560
|
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: ALA (historical) | Statement: [Alcatel, tickerSymbol, ALA (historical)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ALA (historical) Context triple: [Alcatel, tickerSymbol, ALA (historical)]
-
A.
ALA
ALA is the three-letter ISO 3166-1 country code assigned to the autonomous Åland Islands region of Finland.
-
B.
ALA
ALA is the IATA airport code for Almaty International Airport, the main air gateway to Almaty, Kazakhstan.
-
C.
AL
AL is the common abbreviation for the American League, one of the two major professional baseball leagues that make up Major League Baseball in the United States and Canada.
-
D.
AL
AL is the official postal abbreviation for the Brazilian state of Alagoas, located in the country's Northeast region.
-
E.
ALLEA
ALLEA (All European Academies) is a European federation that brings together national academies of sciences and humanities to promote science, scholarship, and evidence-based policy across Europe.
- 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: ALA (historical) Triple: [Alcatel, tickerSymbol, ALA (historical)]
Generated description
ALA (historical) was the former stock ticker symbol used to represent the French telecommunications company Alcatel on securities exchanges.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: ALA (historical) Target entity description: ALA (historical) was the former stock ticker symbol used to represent the French telecommunications company Alcatel on securities exchanges.
-
A.
ALA
ALA is the three-letter ISO 3166-1 country code assigned to the autonomous Åland Islands region of Finland.
-
B.
ALA
ALA is the IATA airport code for Almaty International Airport, the main air gateway to Almaty, Kazakhstan.
-
C.
AL
AL is the common abbreviation for the American League, one of the two major professional baseball leagues that make up Major League Baseball in the United States and Canada.
-
D.
AL
AL is the official postal abbreviation for the Brazilian state of Alagoas, located in the country's Northeast region.
-
E.
ALLEA
ALLEA (All European Academies) is a European federation that brings together national academies of sciences and humanities to promote science, scholarship, and evidence-based policy across Europe.
- 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_69ab495622948190bc6bc6e4cddaf645 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abc94d048481908409d60129aef747 |
completed | March 7, 2026, 6:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aebf4a784c819082c47e3936242478 |
completed | March 9, 2026, 12:38 p.m. |
| NEDg | Description generation | batch_69aec28e0e38819085027240e2b3eb1b |
completed | March 9, 2026, 12:52 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69aec34a9a0481908c1033cb7d4b1516 |
completed | March 9, 2026, 12:55 p.m. |
Created at: March 6, 2026, 9:42 p.m.