Triple
T16294661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L'Étang-la-Ville |
E395614
|
entity |
| Predicate | commutersTo |
P61070
|
FINISHED |
| Object | Paris |
E568
|
NE FINISHED |
How this triple was built (3 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: Paris | Statement: [L'Étang-la-Ville, commutersTo, Paris]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paris Context triple: [L'Étang-la-Ville, commutersTo, Paris]
-
A.
Paris
chosen
Paris is the capital and largest city of France, renowned for its historic architecture, art, fashion, and cultural influence worldwide.
-
B.
Paris
Paris is a prince of Troy in Greek mythology, best known for judging the beauty contest of the goddesses and for abducting Helen, which sparked the Trojan War.
-
C.
Paris
Paris is a major Chilean department store and retail chain offering a wide range of apparel, home goods, and consumer products.
-
D.
Paris
Paris is a budget-oriented AMD Sempron processor core designed for entry-level desktop computing.
-
E.
Paris
Paris was an enslaved man held in bondage by George Washington at the President's House in Philadelphia during his presidency.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commutersTo Context triple: [L'Étang-la-Ville, commutersTo, Paris]
-
A.
commuterServiceTo
Indicates a transportation service that regularly carries commuters to a specified destination.
-
B.
commuterDestination
chosen
Indicates that a location serves as the endpoint or target place to which a person regularly travels for commuting.
-
C.
commuterHubFor
Indicates a location that serves as a primary transit or gathering point for commuters traveling to or from another place.
-
D.
commutesBetween
Indicates a regular pattern of travel back and forth between two locations, typically for work, study, or routine activities.
-
E.
usedByCommuters
Indicates that something is regularly utilized by people traveling between home and work or school.
- F. None of above.
Provenance (4 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_69d87f22c7248190a54c949738441e2e |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e25e2c255881909d99c43770475329 |
completed | April 17, 2026, 4:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a003550fc0c8190ba78666da8b3cd81 |
completed | May 10, 2026, 7:35 a.m. |
| PD | Predicate disambiguation | batch_69e219fa5508819097e9d383348bf174 |
completed | April 17, 2026, 11:31 a.m. |
Created at: April 10, 2026, 5:05 a.m.