Triple
T15096149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FWONA |
E360542
|
entity |
| Predicate | hasRelatedTicker |
P45350
|
FINISHED |
| Object |
FWONB
FWONB is a class of Liberty Media Formula One Group tracking stock that represents economic interests in the Formula 1 motor racing business.
|
E1137605
|
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: FWONB | Statement: [FWONA, hasRelatedTicker, FWONB]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FWONB Context triple: [FWONA, hasRelatedTicker, FWONB]
-
A.
FWN
FWN is the standard abbreviation used for the Fort Wayne TinCaps, a Minor League Baseball team based in Fort Wayne, Indiana.
-
B.
FWN
FWN is the Dutch abbreviation for the Faculty of Science at Leiden University, a major academic division focused on scientific research and education.
-
C.
FW
FW refers to the Free Voters (Freie Wähler), a German political association and party known for its strong local-government focus and presence in Bavarian municipal and regional politics.
-
D.
FW
FW is the designation used for the series of Formula One racing car chassis developed and raced by the Williams Grand Prix Engineering team.
-
E.
FW
FW is the IATA airline designator assigned to the Japanese regional carrier Ibex Airlines.
- 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: FWONB Triple: [FWONA, hasRelatedTicker, FWONB]
Generated description
FWONB is a class of Liberty Media Formula One Group tracking stock that represents economic interests in the Formula 1 motor racing business.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: FWONB Target entity description: FWONB is a class of Liberty Media Formula One Group tracking stock that represents economic interests in the Formula 1 motor racing business.
-
A.
FWN
FWN is the standard abbreviation used for the Fort Wayne TinCaps, a Minor League Baseball team based in Fort Wayne, Indiana.
-
B.
FWN
FWN is the Dutch abbreviation for the Faculty of Science at Leiden University, a major academic division focused on scientific research and education.
-
C.
FW
FW refers to the Free Voters (Freie Wähler), a German political association and party known for its strong local-government focus and presence in Bavarian municipal and regional politics.
-
D.
FW
FW is the designation used for the series of Formula One racing car chassis developed and raced by the Williams Grand Prix Engineering team.
-
E.
FW
FW is the IATA airline designator assigned to the Japanese regional carrier Ibex Airlines.
- 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_69d85a035aa88190b52a139d3a1b7b6d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e005466e9c8190a68e1fbeb8922b1a |
completed | April 15, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feae21134c81908939ad6ce46703d8 |
completed | May 9, 2026, 3:46 a.m. |
| NEDg | Description generation | batch_69feb37427a881908cf95f60b06251d4 |
completed | May 9, 2026, 4:09 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69feb429517c8190a91cc6b50345d889 |
completed | May 9, 2026, 4:12 a.m. |
Created at: April 10, 2026, 3:04 a.m.