Triple
T16058362
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Firefly |
E389540
|
entity |
| Predicate | ICAOcode |
P419
|
FINISHED |
| Object |
FFM
FFM is the ICAO airline designator assigned to Firefly, a Malaysian regional airline and subsidiary of Malaysia Airlines.
|
E1191846
|
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: FFM | Statement: [Firefly, ICAOcode, FFM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FFM Context triple: [Firefly, ICAOcode, FFM]
-
A.
FFM
FFM is an abbreviation commonly used for the Montreal World Film Festival, an international film festival held annually in Montreal, Canada.
-
B.
FFS
FFS is the state agency responsible for managing and protecting Florida’s forest resources, including wildfire prevention, suppression, and sustainable forestry.
-
C.
FFS
FFS is the commonly used abbreviation for the Swiss Federal Railways, the national railway company of Switzerland.
-
D.
FFS
FFS is a high-performance file system originally developed for BSD Unix that introduced improved disk layout and efficiency over earlier Unix file systems.
-
E.
FFS
FFS is the station code for Frankfurt (Main) Süd, a major railway station in Frankfurt, Germany.
- 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: FFM Triple: [Firefly, ICAOcode, FFM]
Generated description
FFM is the ICAO airline designator assigned to Firefly, a Malaysian regional airline and subsidiary of Malaysia Airlines.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: FFM Target entity description: FFM is the ICAO airline designator assigned to Firefly, a Malaysian regional airline and subsidiary of Malaysia Airlines.
-
A.
FFM
FFM is an abbreviation commonly used for the Montreal World Film Festival, an international film festival held annually in Montreal, Canada.
-
B.
FFS
FFS is the commonly used abbreviation for the Swiss Federal Railways, the national railway company of Switzerland.
-
C.
FFS
FFS is the state agency responsible for managing and protecting Florida’s forest resources, including wildfire prevention, suppression, and sustainable forestry.
-
D.
FFS
FFS is a high-performance file system originally developed for BSD Unix that introduced improved disk layout and efficiency over earlier Unix file systems.
-
E.
FFS
FFS is the station code for Frankfurt (Main) Süd, a major railway station in Frankfurt, Germany.
- 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_69d86dae698881908327ef2d67706cb9 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1837634248190a99cc454ad1e99e0 |
completed | April 17, 2026, 12:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffdbe678fc8190b36737a9cd29691c |
completed | May 10, 2026, 1:14 a.m. |
| NEDg | Description generation | batch_69ffdd2e0c38819091a57098985fa19e |
completed | May 10, 2026, 1:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffde20bd488190a06cedf311e37c80 |
completed | May 10, 2026, 1:23 a.m. |
Created at: April 10, 2026, 4:57 a.m.