Triple
T6709135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eisenach |
E153084
|
entity |
| Predicate | twinTown |
P1072
|
FINISHED |
| Object |
Waverly
Waverly is a town that is officially twinned with Eisenach, Germany, reflecting a formal cultural and municipal partnership.
|
E613820
|
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: Waverly | Statement: [Eisenach, twinTown, Waverly]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Waverly Context triple: [Eisenach, twinTown, Waverly]
-
A.
Rochelle
Rochelle is the full given name of Chellie Pingree, an American politician serving as a U.S. Representative from Maine.
-
B.
Fairview
Fairview is a community in Alameda County, California, situated adjacent to the city of Hayward in the San Francisco Bay Area.
-
C.
Fairview
Fairview is a residential neighborhood located within the city of Camden, New Jersey.
-
D.
Harkstead
Harkstead is a small rural village and civil parish in Suffolk, England, situated near the River Stour on the Shotley Peninsula.
-
E.
Laurel
Laurel is a small city in Maryland known for its suburban character and location between Washington, D.C. and Baltimore.
- 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: Waverly Triple: [Eisenach, twinTown, Waverly]
Generated description
Waverly is a town that is officially twinned with Eisenach, Germany, reflecting a formal cultural and municipal partnership.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Waverly Target entity description: Waverly is a town that is officially twinned with Eisenach, Germany, reflecting a formal cultural and municipal partnership.
-
A.
Rochelle
Rochelle is the full given name of Chellie Pingree, an American politician serving as a U.S. Representative from Maine.
-
B.
Fairview
Fairview is a community in Alameda County, California, situated adjacent to the city of Hayward in the San Francisco Bay Area.
-
C.
Fairview
Fairview is a residential neighborhood located within the city of Camden, New Jersey.
-
D.
Harkstead
Harkstead is a small rural village and civil parish in Suffolk, England, situated near the River Stour on the Shotley Peninsula.
-
E.
Laurel
Laurel is a feminine given name of English origin, derived from the laurel tree traditionally associated with honor and victory.
- 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_69c68808d8d8819087369015270788fe |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d105b49c8190932246a727e2c513 |
completed | March 27, 2026, 6:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7008e6b308190a3d5db2bf4a469c4 |
completed | March 27, 2026, 10:11 p.m. |
| NEDg | Description generation | batch_69c701be78cc8190a0848ea60908d129 |
completed | March 27, 2026, 10:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7021b27288190866aef500198479d |
completed | March 27, 2026, 10:18 p.m. |
Created at: March 27, 2026, 2:06 p.m.