Triple
T14072700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tuscaloosa National Airport |
E338650
|
entity |
| Predicate | FAA LID |
P420
|
FINISHED |
| Object |
TCL
TCL is the FAA location identifier code for Tuscaloosa National Airport in Tuscaloosa, Alabama.
|
E1079719
|
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: TCL | Statement: [Tuscaloosa National Airport, FAA LID, TCL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TCL Context triple: [Tuscaloosa National Airport, FAA LID, TCL]
-
A.
TCL
TCL is the public transport network operator serving Lyon and its metropolitan area in France, managing buses, trams, and metro services.
-
B.
TCL Corporation
TCL Corporation is a major Chinese electronics company best known globally for manufacturing televisions and other consumer electronics.
-
C.
Huawei
Huawei is a major Chinese multinational technology company best known globally for its telecommunications equipment, smartphones, and role in 5G network infrastructure.
-
D.
Midea
Midea is an important archaeological site in Greece that was a fortified citadel of the Mycenaean civilization.
-
E.
ZTE
ZTE is a major Chinese telecommunications and technology company known for manufacturing network equipment and smartphones and competing globally with firms like Nokia and Huawei.
- 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: TCL Triple: [Tuscaloosa National Airport, FAA LID, TCL]
Generated description
TCL is the FAA location identifier code for Tuscaloosa National Airport in Tuscaloosa, Alabama.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: TCL Target entity description: TCL is the FAA location identifier code for Tuscaloosa National Airport in Tuscaloosa, Alabama.
-
A.
TCL
TCL is the public transport network operator serving Lyon and its metropolitan area in France, managing buses, trams, and metro services.
-
B.
TCL Corporation
TCL Corporation is a major Chinese electronics company best known globally for manufacturing televisions and other consumer electronics.
-
C.
Huawei
Huawei is a major Chinese multinational technology company best known globally for its telecommunications equipment, smartphones, and role in 5G network infrastructure.
-
D.
Midea
Midea is an important archaeological site in Greece that was a fortified citadel of the Mycenaean civilization.
-
E.
ZTE
ZTE is a major Chinese telecommunications and technology company known for manufacturing network equipment and smartphones and competing globally with firms like Nokia and Huawei.
- 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_69d81c67ba6c819091935650dfb3b895 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5c5aa828819098ef55a70a0decbc |
completed | April 14, 2026, 3:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcd09f69c08190b5cd12f9ff1a3f73 |
completed | May 7, 2026, 5:49 p.m. |
| NEDg | Description generation | batch_69fcd3a8b8e08190b230ab8a2215145e |
completed | May 7, 2026, 6:02 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fcd48acddc819087d626c4764bf148 |
completed | May 7, 2026, 6:06 p.m. |
Created at: April 9, 2026, 10:21 p.m.