Triple
T16989296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Operation Teapot |
E412149
|
entity |
| Predicate | codename |
P2980
|
FINISHED |
| Object |
Teapot
Teapot is a type of vessel, typically made of ceramic or metal, designed for brewing and serving tea.
|
E1244966
|
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: Teapot | Statement: [Operation Teapot, codename, Teapot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Teapot Context triple: [Operation Teapot, codename, Teapot]
-
A.
the Teapot
The Teapot is a prominent asterism in the constellation Sagittarius whose stars outline the shape of a traditional teapot in the night sky.
-
B.
Teakettle
Teakettle is a small village in the Cayo District of central Belize, known as a rural community along the George Price Highway near the Belize River.
-
C.
Ma Kettle
Ma Kettle is a comically rustic, good-natured farm wife character from the popular mid-20th-century "Ma and Pa Kettle" film series.
-
D.
Tumbler
Tumbler was a series of early 1950s U.S. nuclear weapons tests conducted at the Nevada Test Site to study blast and radiation effects.
-
E.
Tumbler
Tumbler is a close associate and ally of master car thief Memphis Raines in the action film "Gone in 60 Seconds."
- 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: Teapot Triple: [Operation Teapot, codename, Teapot]
Generated description
Teapot is a type of vessel, typically made of ceramic or metal, designed for brewing and serving tea.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Teapot Target entity description: Teapot is a type of vessel, typically made of ceramic or metal, designed for brewing and serving tea.
-
A.
the Teapot
The Teapot is a prominent asterism in the constellation Sagittarius whose stars outline the shape of a traditional teapot in the night sky.
-
B.
Teakettle
Teakettle is a small village in the Cayo District of central Belize, known as a rural community along the George Price Highway near the Belize River.
-
C.
Ma Kettle
Ma Kettle is a comically rustic, good-natured farm wife character from the popular mid-20th-century "Ma and Pa Kettle" film series.
-
D.
Tumbler
Tumbler was a series of early 1950s U.S. nuclear weapons tests conducted at the Nevada Test Site to study blast and radiation effects.
-
E.
Tumbler
Tumbler is a close associate and ally of master car thief Memphis Raines in the action film "Gone in 60 Seconds."
- 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_69d886cb581c8190ab05f4b429c9cd85 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d27dca248190a9b73b16439d5631 |
completed | April 18, 2026, 6:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00dc12e308819093e7f8933cdd6ba9 |
completed | May 10, 2026, 7:27 p.m. |
| NEDg | Description generation | batch_6a0114d5aeb0819086f1a5d279ac0d0f |
completed | May 10, 2026, 11:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0115c967b0819088e2335fd45d755b |
completed | May 10, 2026, 11:33 p.m. |
Created at: April 10, 2026, 5:32 a.m.