Triple
T2175223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GML |
E48510
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object |
WFS
WFS (Web Feature Service) is an OGC standard web service that provides access to and manipulation of geographic features over the internet in vector form.
|
E242850
|
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: WFS | Statement: [GML, relatedTo, WFS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WFS Context triple: [GML, relatedTo, WFS]
-
A.
WSF
WSF is the vehicle registration code used on license plates for the Burgenlandkreis district in the German state of Saxony-Anhalt.
-
B.
WSF
WSF is the commonly used abbreviation for Washington State Ferries, the largest ferry system in the United States serving routes across Puget Sound and nearby waterways.
-
C.
FWS
FWS is a U.S. federal financial aid program that provides part-time jobs to eligible college students to help them pay for educational expenses.
-
D.
WF
WF is the common abbreviation for Wikifunctions, a Wikimedia project aimed at creating a collaborative catalog of reusable functions.
-
E.
FGw
FGw is the Faculty of Humanities at the University of Amsterdam, encompassing disciplines such as languages, history, philosophy, arts, and cultural studies.
- 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: WFS Triple: [GML, relatedTo, WFS]
Generated description
WFS (Web Feature Service) is an OGC standard web service that provides access to and manipulation of geographic features over the internet in vector form.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: WFS Target entity description: WFS (Web Feature Service) is an OGC standard web service that provides access to and manipulation of geographic features over the internet in vector form.
-
A.
WSF
WSF is the vehicle registration code used on license plates for the Burgenlandkreis district in the German state of Saxony-Anhalt.
-
B.
WSF
WSF is the commonly used abbreviation for Washington State Ferries, the largest ferry system in the United States serving routes across Puget Sound and nearby waterways.
-
C.
FWS
FWS is a U.S. federal financial aid program that provides part-time jobs to eligible college students to help them pay for educational expenses.
-
D.
WF
WF is the common abbreviation for Wikifunctions, a Wikimedia project aimed at creating a collaborative catalog of reusable functions.
-
E.
FGw
FGw is the Faculty of Humanities at the University of Amsterdam, encompassing disciplines such as languages, history, philosophy, arts, and cultural studies.
- 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_69a88aa3faa48190995b233af6525815 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbece30888190936853740ff6cb02 |
completed | March 7, 2026, 5:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae5d9eff988190a02734bd73616cba |
completed | March 9, 2026, 5:41 a.m. |
| NEDg | Description generation | batch_69ae5e5f023081909cd046b5850f8026 |
completed | March 9, 2026, 5:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae5ef99018819083a778378ea493e8 |
completed | March 9, 2026, 5:47 a.m. |
Created at: March 4, 2026, 7:45 p.m.